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Machine-to-Machine Communication: An Overview of Opportunities
Accepted Manuscript
Machine-to-Machine Communication: An Overview of Opportunities Oluwatosin Ahmed Amodu, Mohamed Othman PII: DOI: Reference:
S1389-1286(18)30851-X https://doi.org/10.1016/j.comnet.2018.09.001 COMPNW 6583
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Computer Networks
Received date: Revised date: Accepted date:
21 February 2018 6 August 2018 2 September 2018
Please cite this article as: Oluwatosin Ahmed Amodu, Mohamed Othman, Machine-toMachine Communication: An Overview of Opportunities, Computer Networks (2018), doi: https://doi.org/10.1016/j.comnet.2018.09.001
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Machine-to-Machine Communication: An Overview of Opportunities
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Oluwatosin Ahmed Amodu∗, Mohamed Othman
Department of Communication Technology and Network, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor Darul Ehsan, Malaysia.
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Abstract
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The envisioned capability of machine devices to autonomously communicate in the future Internet of Things (IoT) has brought considerable attention to machine-to-machine (M2M) communication in recent years. This paradigm has applications in homes, safety, transport, health, and industry. As an active focus of research, there are interesting open questions on several of its aspects, which we aim to capture in this paper. Accompanied by an attempted classification of existing surveys on M2M, we propose a followable exposition on the challenges and open research opportunities that embrace the diverse facets of M2M.
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Keywords: access problems, applications, challenges, home, mobile, open issues, standards, survey, taxonomy, technologies, M2M, MAC.
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1. Introduction
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Machine-to-Machine (M2M) communication is the autonomous interaction of a large number of machine devices to perform sensing, processing, and actuation activities without human intervention. These devices include meters in a smart grid, electronics and servers, and navigation sensors used for relaying information through a network. The main feature that sets M2M apart from other communication paradigms is the absence of human supervision [1, 2, 3, 4, 5]. The primary objective of M2M communication is to ∗
Corresponding author Email addresses: [email protected] (Oluwatosin Ahmed Amodu), [email protected]; [email protected] (Mohamed Othman)
Preprint submitted to Computer Networks
September 3, 2018
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• The emergent automation of machine devices
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enable communication among smart devices [6]. This fast-growing paradigm with billions of inter-connected machines used for various applications is imminent [7]. M2M has been a focus of extensive research in recent years because of several reasons. Some of the reasons and enablers of M2M include [5, 7, 8, 9, 10, 11]:
• The pervasiveness of high-speed internet access
• The declining cost of sensing and actuating devices
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• The cheap, ubiquitous connectivity of electronic gadgets • The utility and variety of M2M applications
• The projected impact of M2M communication on cellular network connections and the growth rate • The use of machine devices in locations unfrequented by humans
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• The potential of M2M communication in generating revenue for cellular operators
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M2M applications span across various fields such as health, monitoring, security, home, and city automation. To facilitate such autonomous communication, several challenges must be addressed in different areas. Among other reasons, these challenges emerge from the unique characteristics of M2M communication in different architectural domains and its diverse applications. In this paper, we present the challenges and opportunities associated with various aspects of M2M communication shown in Figure 1, which is based on the emphasis placed on such aspects in the existing literature (see Figure 2). We provide a high-level summary of relevant literature in each aspect, indicating some other related articles, to familiarise readers with other recent research. The organisation of the main sections of this paper (Sections 2 to 7) is shown in Figure 3. A more general approach to classifying M2M communication is to categorise it into cellular and capillary M2M communication as presented in [12]. However, our discussion in this paper emphasises the aspects of the research in the literature from different perspectives such as application use cases. 2
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Figure 1: Classification of themes for M2M communication
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It is worth noting that the classified aspects in this paper are not fully orthogonal because the objective is to emphasise the opportunities that are available based on a careful study of existing surveys in this field. For instance, Long-Term Evolution (LTE)/Long-Term Evolution-Advanced (LTEA) can be classified as a standard but we have included LTE/LTE-A as a separate section for emphasis. Furthermore, [7, 12, 13] could have assumed a more general classification but a key aspect in each survey was considered. Our findings demonstrate that as the number of existing surveys increase, it is essential to capture some of the key efforts that have been presented in such surveys. Therefore, we present Figures 4, 5 and 6. 3
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Figures 4 and 5 classify summary tables presented in these references, guiding the interested reader to associated references for subjects of interest. For example, a reader can find an ‘overview of contention-based channel access mechanisms in various communication technologies for IoT’ under medium access in Figure 5 in reference [14]. Similarly, Figure 6 guides readers to cardinal illustrations (such as architectures) in the literature. The remainder of this paper is organised as follows: Section 2 examines issues related to medium access of the M2M wireless channel. Section 3 discusses M2M architecture and technologies associated with home applications. Section 4 provides insights into M2M for mobile deployments, which includes the challenges, vehicular M2M architecture and related issues. Section 5 explores several standardisation efforts in M2M/IoT. Section 6 examines cellular LTE/LTE-A networks and ultra-dense networks (UDNs). Section 7 analyses issues concerning energy efficiency, reliability, and security in M2M with potential solutions. Section 8 concludes this paper. Common notations used in this paper are provided in Table 1 within the appendix.
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2. Medium Access
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As M2M is envisioned to involve millions of machine devices, it presents several challenges in research. One of the fundamental issues of critical concern is the inability of access management mechanisms in traditional wireless networks to accommodate the unprecedented number of projected devices while satisfying the necessary quality of service (QoS) requirements. In this section, we will discuss the fundamental issues pertaining to medium access protocols in traditional and cellular networks, including their pros and cons. Considerations for choosing or designing protocols and open issues will be discussed.
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2.1. MAC protocols for M2M Medium access control (MAC) schemes define the rules which allow devices to communicate with each other in an orderly and efficient manner [35]. The development of MAC protocols plays a vital role in the pursuit of autonomous machine communication. Generally, traditional MAC protocols can be broadly categorised into three classes, namely contentionbased, contention-free, and hybrid schemes. These three schemes differ in the approach by which transmission time slots are acquired and managed. In contention-based schemes, nodes contend for access to the shared medium. 4
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Figure 2: Taxonomy of survey papers for M2M communication
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Whenever any node acquires the channel, it transmits at a specific time slot. The node defers transmission if the channel is busy. If the state of the channel is empty, the node transmits or backs-off for a random time before it transmits [16]. Contention-free schemes, on the other hand, have pre-allocated time slots for each node to transmit. Hybrid schemes combine both contention-based and contention-free schemes. Contention-based schemes do not scale at high loads i.e. their performance degrades with an increase in the number of nodes. Contention-based schemes are also not energy-efficient as the retransmission of packets leads to energy loss. Another issue is that in contention-based schemes where nodes back-off because of contention, the back-off parameters are selected based on the traffic load. Clearly, this may not be efficient in applications where 5
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Introduction
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A primer to introduce each aspect
Discussion on key aspects
Main Section
Subsections
Future considerations
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Relevant Literature
Main references and other associated references
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Figure 3: Organisation of main sections in this paper
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delay-critical information must be shared for safety as in the case of sharing information between pedestrians, vehicles, and road infrastructure [14]. On the contrary, contention-free schemes are more energy efficient and possess better scalability. However, they cannot adapt to dynamic network conditions because node transmission occurs at scheduled time slots. Delay is also incurred since devices would have to wait for their assigned time slots. The use of hybrid schemes, which combine the advantages of the above approaches and offset the demerits, have also been considered in the wireless networks (adhoc and sensor network) literature [36] and recently for M2M [37, 38, 39]. In terms of the fraction of channel capacity deployed for data transmission i.e. throughput, hybrid schemes generally perform better than contention-based schemes (especially at high loads). However, hybrid schemes still incur longer delays as compared with contention-free schemes e.g. Time Division Multiple Access (TDMA) for lesser number of devices in [37, 38]. Tree-based schemes such as the distributed queuing (DQ) algorithm [41] where a group of contending devices are iteratively split to smaller subgroups 6
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to reduce collisions, have been studied and found suitable for M2M networks [40]. Specifically, the DQ algorithm achieves fairness and scalability for an unlimited number of devices [14, 15]. Recently, a hybrid collision avoidance tree-resolution mechanism was proposed in [42]. The scheme demonstrates better performance compared with collision avoidance mechanisms without the tree-based access. [43] proposed a hybrid of adaptive slotted-ALOHA and TDMA to achieve resource utilisation in LTE/LTE-A under strict fairness constraints. The authors [44] proposed a hybrid of slotted-CSMA and TDMA for massive IoT devices. The algorithm caters to an efficient registration of up to eight thousand devices when these devices attempt to register at one centralized access point. [45] combines contention and contention-free mechanisms to address preamble collision in LTE because of periodic machine access. A number of further directions associated with the MAC layer includes [8, 16]: • Handling scalability for massive machine device connections; • Designing MAC layer schedulers for M2M applications;
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• Incorporating low power communication into scalable MAC protocol design;
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• Supporting priority access for applications such as alarming applications by supporting differentiated bandwidth requests, resource reservation, admission control, and priority-based service pre-emption;
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• Devising support for diverse QoS requirements; • Deploying heterogeneous transceivers;
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• Designing MAC protocols that support multi-hop architectures; • Developing energy-harvesting aware MAC protocols;
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• Devising support for clustering at the MAC layer; • Supporting new technologies like wake-up radio; • Designing mobility-aware MAC protocols; • Devising support for intra-M2M connectivity at the MAC layer. 7
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Apart from the above issues related to the MAC layer, cross-layer optimisation should be intuitively enhanced in a manner that is independent of the production of new commercial hardware [7].
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Relevant Literature In the survey entitled ‘A Survey of MAC layer Issues and Protocols for Machine-to-Machine Communications’ [8], the authors highlighted the key characteristics of MAC protocols for M2M communication with a focus on ensuring scalable, efficient, and fair channel access for machine devices. They discussed MAC protocols specifically proposed for M2M communication. Limitations for [46, 47, 48] were highlighted; however, no critique was presented for [49, 50, 51]. Future work is required to extend the proposed taxonomy for medium access proposals with the inclusion of tree-based contention resolution, energy-harvesting protocols, and other recent proposals. Among others, this work has been referenced in [52, 53, 54, 55]. Authors in [52] presented a comprehensive survey of fog and cloud Radio Access Network (RAN) for 5th Generation wireless system (5G) networks; investigating a synergy of these two architectures for the diverse needs of 5G mobile networks. [53] designed a random access scheme for M2M data transmission in applications with delay constraints. The protocol inherits the benefits of DQ’s collision resolution as well as the efficiency of the data transmission in Multiple-input and Multiple-output (MIMO). Recently, [54] proposed an intelligent CSMA-based collision avoidance mechanism suitable for capillary M2M communication characterised by low power and short-range transmissions. [55] studied a multi-channel CSMA for M2M communication. They show that the traffic load defines the gains in energy efficiency and delay achieved when the frequency band is divided into sub-bands Laya et al. considered the MAC solutions for IoT in the article ‘Goodbye Aloha!’ [14]. They presented the DQ protocol, demonstrating that it works for an infinite number of machine devices regardless of the network load and traffic pattern. A major contribution is its invitation of the research community to consider an alternative to the current ALOHA-based protocols for deployment in IoT. This paper has been referred to in [56, 57, 58]. Reference [56] surveyed low power wide area (LPWA) networks and [57] reviewed LTE random access channel (RACH) for IoT, evaluating the performance of 3rd Generation Partnership Project (3GPP) schemes for overload control. Similarly, [58] addressed preamble collision for massive smart devices using the preamble grouping method. 8
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Recently, [16] presented ‘A survey of hybrid MAC protocols for machineto-machine communications’. The paper focused on peculiar areas pertaining to a recent trend in MAC protocol design for M2M by providing insights into the objectives and problems solved in different protocols while revealing enhancement opportunities and potential future directions. Some of the future directions identified include the use of directional antennas, wake-up radios, energy-harvesting and multi-hop MAC protocols.
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2.2. Access Management for Cellular M2M In cellular networks, devices also contend for access to the wireless channel. Because M2M networks consist of a massive number of devices, this necessitates the consideration of a highly effective contention resolution procedure i.e. an approach by which transmission collision can be resolved to ensure the effective utilisation of wireless radio resources. For example, there is a standard random access (RA) procedure that defines how devices attempt to access the channel and mechanisms for handling collisions in LTE. This procedure is necessary because devices contend while requesting for transmission or during reconnection after a failure. Measures that can be used for evaluation and performance comparisons of access management techniques for M2M in cellular networks include access delay, transmission success rate, energy efficiency and QoS guarantee of machine devices. These metrics can be defined as follows [5]:
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• Access delay refers to the length of time between the initiation and completion of random access procedure. • Success rate refers to the rate by which random access attempts are successful considering the maximum number retransmissions allowable.
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• Energy Efficiency refers to the total amount of energy which is spent during the access management process.
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• QoS guarantee refers to the ability of machine devices to meet peculiar service requirements such as delay.
With regards to the above mentioned measures, it is highly desired that devices are not delayed access beyond the application QoS constraint. The rate of transmission success should also be high. Another important factor to be considered is device mobility. For example, in applications such as 9
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Figure 4: Summary tables in literature and their references
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Figure 5: Summary tables in literature and their references
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vehicular M2M, the mobility of devices should be accommodated effectively without negatively impacting the overall QoS of the network. Solutions for medium access management were proposed by 3GPP for M2M communication in a cellular architecture. Solutions include access barring schemes, separation of RACH resources, dynamic allocation of RACH resources, back-off schemes, slotted access schemes, and pull-based schemes (where machine type communication devices (MTCDs) transmit data to eNB only when they are paged [59]) [5]. Suggesting that RACH contention is caused by high preamble transmission rate, [60] proposed a two-stage scheme based on controlling preamble transmission rates. The first stage is an auction approach for balancing and allocating traffic among periods, while the second stage is an RACH attempt estimation approach for controlling the preamble transmission rate decided by the first stage. For a variety of M2M applications, the proposed scheme is capable of handling access requests effectively. Some research directions are to [5, 61]:
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• investigate if a trade-off exists (and to what extent) between computation and communication costs for maintaining a clustered M2M network;
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• design energy-efficient access management protocols for event-driven applications;
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• ensure the availability of adequate control channel resources for massive M2M in cellular networks;
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• research the desired cluster size for massive hierarchical M2M in different settings; • address core network (CN) scaling or signalling because of congestion caused by concurrent signalling messages of machine devices;
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• develop hybrid pricing schemes to cater to the simultaneous access of machine and human traffic; • design LTE schedulers that can accommodate timing constraints and specific QoS requirements (latency, jitter, and guaranteed bit rate) for M2M communication within the Transmission Time Interval (TTI) of LTE; 12
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• design low-complexity schedulers for M2M in LTE/LTE-A;
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• design schedulers capable of catering to real and non-real time applications.
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Relevant Literature In ‘A survey of access management techniques in machine type communications’, [5] compared and classified several access management proposals for M2M communication based on metrics such as success rate, access delay, energy-efficiency, and QoS guarantees. This article has influenced other works including [43, 62, 63, 64, 65]. Reference [43] proposed a hybrid of adaptive slotted-ALOHA and TDMA to achieve resource utilisation in LTE/LTE-A under strict fairness constraints. Reference [62] presents an RA procedure for achieving resource efficiency and increased number of successful accesses. In [63], issues and proposed solutions for RAN and CN overload because of massive machine access are surveyed. Authors in [64] proposed a dynamic scheduler for LTE uplink that adjusts to network contention levels using traffic information. The scheduler supports M2M traffic and controls the impact of the Human-to-Human (H2H) traffic performance. Reference [65] presented a framework for analysing one-stage massive access. Using two approaches, the authors modelled and evaluated the channel occupancy rate and success probability. In the first approach, transmission from the devices arrive at the evolved Node B (eNB) with the same average received power. The second approach is Signal-to-interference-plus-noise (SINR)-based; where it was assumed that devices transmit with a constant power i.e. using channel inversion power control. The authors used analytical and Monte-Carlo simulation approaches to verify the results. The article ‘Is the random access channel of LTE and LTE-A suitable for M2M communications? A survey of alternatives’ [15], summarised the pros, cons, and future trends associated with alternative schemes proposed for improving LTE/LTE-A RACH operations. The authors expounded on the performance of the RACH in terms of energy efficiency to serve as a benchmark for future energy-efficient protocol designs. This article has also been referred to in [66, 67, 68, 69, 70, 71, 72, 73]. Authors in [66] studied the limit of M2M and H2H coexistence in LTE networks using thorough system level simulations. [69] focused on the physical layer (PHY) and MAC transmission technologies for IoT by comparing their performances. 13
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Recently, [70] considered RA in M2M communication with QoS, whereas [71] discussed machine type communication (MTC) with respect to its associated requirements, challenges, and solutions. [72] proposed an analytical framework for optimizing the random access performance of M2M communication. [73] presented a random access protocol based on DQ, with an estimation mechanism which can cater to over ten thousand simultaneous arrivals of traffic. In the article entitled ‘A survey of Traffic Issues in Machine-to-Machine communications over LTE’, [17] reviewed and classified proposed mechanisms for solving access traffic issues and traffic simulation models in the literature. Amongst others, [42, 74, 75, 76] have referred to this work. Reference [74] proposed a system for home automation suitable for large transducer deployment. The proposed system quickly recognises and configures transducers, thereby saving setup time and resources. For massive machine type devices (MTDs), [75] studied the design of uplink transmission for very short delay and high reliability requirements in tactile internet. Likewise, reference [42] considers a hybrid of collision avoidance and tree collision resolution in LTE for synchronised traffic in aircraft applications. Recently, [76] discussed issues relating to signalling and resource scheduling in LTE-based M2M/IoT networks characterised by small data transmissions. In this respect they reviewed literature on resource allocation in these networks. They further modelled the optimal behaviour of their previously proposed algorithm in [118]. According to the authors, a possible extension of this work is an evaluation of the energy-saved by the algorithm for M2M devices with small data transmissions. In ‘Classification of LTE Uplink Scheduling Techniques: An M2M Perspective’ [61], the authors surveyed uplink scheduling techniques for M2M over LTE/LTE-A and presented a classification of LTE scheduling techniques based on multi-hop and scalability, QoS parameters, and power savings. A main contribution is its exposition of different schedulers for LTE-A and the complexity of various scheduling algorithms. Amongst others, [61] has been referred to in [78, 79]. Reference [78] introduced a scheduling metric called ‘Statistical Priority’, which demonstrates the peculiarity of some packets sent by MTCDs. Data with non-redundant information is scheduled with a higher priority to properly manage radio resources. This approach results in a lower number of deadline misses for critical data. The authors in [79] modelled the energy consumed, and investigated the impact of scheduling and power control on the battery lifetime of machine devices in cellular-based 14
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M2M networks.
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2.3. Access Management for Capillary M2M A capillary network is a local network which deploys short-range radioaccess technologies to provide connectivity to groups of devices [80]. Capillary M2M network consists of machine devices supporting technologies such as Zigbee, Bluetooth, WiFi, ultra-wide band (UWB) and Smart Utility Networks (SUNs). The network uses Industrial Scientific Medical (ISM) band which eradicates the problem of interference with cellular users. Capillary M2M can also ‘aggregate and shape’ M2M traffic transported to a wired, wireless or cellular network such as WiMAX and LTE [81]. Capillary M2M networks have advantages over cellular M2M networks, considering peculiar perspectives. For instance, devices can connect to free unlicensed band radio access technology (RAT) in capillary networks. Although, cellular M2M networks enjoy highly reliable communication and wider coverage, capillary M2M can be effectively deployed in areas with poor cellular coverage such as basements and indoor environments. ZigBee can be effectively deployed in smart homes as it can cater to low power and low-rate applications, whereas Bluetooth Low Energy (BLE) can be effectively used in home automation because of its ultra-low power consumption [18]. Capillary M2M networks are also cost-effective for handling a large number of M2M devices as compared to cellular M2M [82]. Generally, the unique characteristics and general requirements of M2M must be considered when choosing the appropriate technology for access management and during protocol design. Wireless Fidelity (Wi-Fi) for instance has a current service range of 100 m in Wireless Local Area Networks (WLANs), which is quite short to cater to densely deployed MTCDs in large outdoor environments. Therefore, IEEE 802.11ah (Wi-Fi HaLoW) catering to diverse QoS requirements can be integrated into Wi-Fi products, since it can be flexibly configured for different applications [18]. Currently, IEEE 802.11 is one of the wireless technologies being modified for use in IoT because of its wide-range deployment and support for IP connectivity. Therefore, it is promising for energy-efficient and low-cost wide-scale M2M deployment as affirmed in [83]. Some of the issues associated with specific access management in capillary M2M technologies are as follows [18, 81]: • Wi-Fi: Wi-Fi may not fully satisfy the diverse QoS requirements for MTC, it may have to be modified to suit different use-cases. 15
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• IEEE 802.11 standard: Customised solutions for IEEE 802.11 may have to be devised to cater to diverse MTCD applications.
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• ZigBee: Mesh ZigBee networks are characterised by low utilisation as they have no beacons. Tree-based topologies also have limitations which manifest in a lower transmission efficiency and tight synchronisation. Asides the aforementioned, future extensions to these networks should also consider effects of interference, fading and channel quality.
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• Bluetooth: This has energy management issues as well as terminal grouping and data aggregation when M2M terminals are to connect in a piconet (network devices connecting via Bluetooth) [81] as investigated in [84, 85].
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• Coexisting RATs: For the coexistence of technologies such as ZigBee, SUNs, and Wi-Fi, sharing the unlicensed band radio resources is critical and requires proper management. RATs must coexist in a manner that ensures minimum interference [18]. In addressing interference which could occur due to the coexistence of IEEE 802.15.4 and WiFi, inactive periods in the WiFi channels could be exploited [81].
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In addition to the above mentioned issues, it is important to reiterate that these capillary technologies should be able to support heavy M2M traffic in areas such as residential and business areas. Also, MAC protocols which can function with terminals with multiple radio interfaces (such as IEEE 802.11 and IEEE 802.15.4) should also be developed, so that devices can then use whichever technology provides the best connectivity. TV white space could also be deployed to extend the transmission range, especially in less populated areas. Finally, data aggregation should also be supported in gateways for capillary network [81].
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Relevant Literature In the article ‘Radio Resource Management in Machine-to-Machine Communications - A Survey’ by Xia et al.[18], the authors presented a comprehensive survey of research activities related to access control, power management, and radio resource allocation for M2M communication. A detailed discussion on unlicensed band RATs for capillary M2M communication was provided. A unique contribution of this paper is its categorisation of themes for radio resource management in LTE/LTE-A. The authors also identified 16
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open directions with respect to NB-IoT, Sparse Code Multiple Access 1 and software defined network (SDN)-based M2M, amongst others. In the paper entitled ‘Physical layer architectures for machine type communication networks - a survey’ [82] discussed the PHY features of capillary technologies such as Wi-Fi, Bluetooth, ZigBee, and SUN. They proposed an air-link design based on complementary-coded code division multiple access (CC-CDMA). This is suitable for the gateway to small-cell access point interfaces and serves as a ‘complement’ to current standards and technologies. With respect to this, the authors also reviewed CC-CDMA and M2M challenges for future wireless communication. Wang et al.[88] surveyed LPWA, IEEE 802.11ah, and cellular network infrastructure solutions for M2M in the paper entitled ‘A survey of enabling technologies of low power and long-range machine-to-machine communications’. Research gaps and future directions were identified to improve the performance of these low power and long-range technologies. Further related works to [88] include [81, 82, 89, 90]. The authors in [81] discussed the current challenges of capillary M2M communication technologies such as the development of charging policies for service providers and addressing security issues. [89] surveyed technical aspects and use-cases of future IoT-based healthcare applications. In light of this, the authors examined current and emerging technologies, standards, and requirements for such applications with special attention on short and long-range communications. They concluded that an amalgam of existing technologies would be required to cater for future healthcare application. The authors in [90] performed an experimental study to analyse the signalling overhead for M2M services suitable for smart metering and vehicular applications. They proposed techniques for signal reduction by considering signal aggregation to tackle issues associated with a surge in signal overloads.
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3. Home M2M M2M communication has a variety of applications in homes. Examples include surveillance, multimedia streaming and sharing, and energy management systems for smart grid and healthcare. When considering radio service 1 Sparse Code Multiple Access [86] can be regarded as a code division multiple access scheme characterized by sparse codebooks [87]
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Figure 6: Key illustrations in the literature and their references
range and applications, home networks involve body, personal, and local sub-area networks [21].
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3.1. Architecture According to 3GPP, network terminals interconnect in two ways, either cellular or capillary M2M communication. In the first case, M2M terminals directly connect to the cellular (3G or 4G) network. In capillary networks, devices connect using wireless links and data is relayed to the cellular network using a gateway [21, 91]. As shown in Fig.7, the cellular M2M architecture is basically composed of three major components such as machine devices, gateway, and eNodeB. The interaction of these components within the network results in four different forms of communication: devices can communicate mutually, they can connect to the gateway or the eNodeB, and the gateway can also communicate with the eNodeB. In this regard, a proper architectural design is required to guarantee the necessary QoS requirements.
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Some trade-offs must be considered in the design of any network architecture. For instance, in a capillary home M2M network, the coverage per device may be very low when compared with cellular M2M. Other issues associated with home M2M network design include radio interference in home areas, unreliable wireless channels because of fluctuation and noise, nature of devices (e.g. heterogeneity and resource constraints), and self-organisation and QoS support [21]. In addition, an architecture with gateways requiring data aggregation should ensure a proper selection of the relay node. In architectures with cognitive gateways, the gateway should be capable of autonomously interacting with the surrounding environment and adaptively changing the transmitter settings when required.
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Relevant Literature Zhang et al. [21] presented a survey entitled ‘Home M2M Networks: Architectures, standards and QoS improvement’ identifying challenges associated with M2M networks. A QoS and resilience -aware cross-layer joint admission and rate control for multimedia sharing was further proposed. An investigation into this approach with a joint design demonstrated that in resource constrained home M2M networks, the proposed method can allocate radio bandwidth intelligently based on the QoS. In addition, the QoS rate control, a unique feature of [21], is its M2M architecture that supports several technologies. This work has been referred to in [92, 93, 94, 95, 96]. Reference [92] classified M2M in terms of context, task, and objective with a review of recent issues and solutions. [93] addressed radio resource allocation for energy-efficiency in cellular M2M. [94] discussed M2M security challenges in 3GPP and potential solutions. [95] focused on latency, energy savings, and reliability for uplink and downlink M2M with performance analysis. Authors in [96] considered reducing uplink requests for M2M using the grouping and compression approach in the gateways.
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3.2. Technologies Home M2M involves the co-existence of several technologies. The technologies can include Bluetooth Low Energy, short-range radio technologies such as ZigBee, and broadband such as UWB. These technologies come with their merits and demerits. For instance, Bluetooth performs well in terms of energy but has latency issues in large deployments. On the contrary, ZigBee can guarantee low power consumption and longer lifetime, thus, it is used in capillary M2M networks. Similarly, broadband technologies such as 19
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UWB and HomeRF provide high throughput at the price of increased energy consumption [22]. Emerging radio technologies applicable in home networks include IEEE 802.15.6, which is used in medical applications for helping the disabled, 60GHz transmission, and visible light communications [22].
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Relevant Literature The article ‘A survey of recent developments in home M2M networks’ [22] discussed M2M technologies and applications such as entertainment and health and energy management. An examination of home M2M network architectures, performance trade-offs associated with designs, and QoS provisioning methodologies were also conducted. This work has been referred to in [97, 98, 99]. [97] surveyed device-to-device communication (D2D) in cellular networks, [98] reviewed networks for home automation, and [99] considered challenges associated with cognitive radio for future mobile networks. Chen and Lien [4] summarised the technologies for achieving highly efficient machine swarm communication in the paper entitled ‘Machine-tomachine communications: Technologies and challenges’. This aims to facilitate a realisation of wireless M2M infrastructure on the cloud with a massive number of machine devices. [4] also highlighted related enabling technologies for wireless M2M communication. This work has been referred to in [100], which studied the interaction between fog computing and D2D communication for low-latency M2M communication to be configured on an LTE-A platform. Reference [101] studied the definition and classification of white spaces for cognitive radio. [102] considered the interference challenge associated with licensed-assisted access in cellular networks. Authors in [103] investigated statistical networking to attain reliability and QoS guarantees. Reference [104] surveyed cognitive technologies and models for improving the efficiency of M2M communication. 4. Mobile M2M
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Mobile smartphones in cellular networks, vehicle-to-vehicle applications [5], and logistics and e-health [23] constitute interesting applications enabled by M2M communication. For instance, smartphones can play a major role by serving as mobile gateways for energy constrained machine devices in applications such as heart monitoring systems, where the smartphones can be used to receive data [11]. As there has been considerable research on
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wireless body area networks, more studies on the use of smartphones in health applications for M2M are required.
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4.1. Mobile M2M in cellular infrastructure Optimising current cellular network solutions for mobile M2M is a matter of necessity [9]. Mobile M2M applications in the context of cellular networks such as LTE and LTE-A can benefit immensely from the cellular architecture in terms of extensive coverage, high reliability, and reduced cost. However, performance degradation should be avoided by ensuring proper spectrum allocation and utilisation. In a bid to achieve spectral efficiency in the network, issues concerning interference must be properly addressed. In addition, scheduling schemes proposed to achieve proper channel utilisation should duly consider traffic differentiation. Using the resource partitioning approach, RA overload2 control should be made to work in tandem with proper back-off procedures and eNodeB selection. Development of energy efficient transmission schemes using smartphones to function as mobile gateways can be achieved through methods such as transmission scheduling, header compression, and data aggregation [11]. However, future research can leverage heterogeneous networks to address this issue. Other relevant issues include [11, 24]:
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• Investigation of how M2M gateways can be used to reduce bandwidth consumption for prompt data collection and aggregation;
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• Maximisation of radio resources by aggregating multiple device traffic using relay nodes;
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• Power consumption optimisation for M2M in cellular networks and optimising trade-offs associated with reachability;
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• Evaluation of resource usage efficiency in mobile M2M communication. For instance, how do diverse traffic patterns from machine devices affect mobile M2M communication?
2 RA overload occurs as a result of massive random access in dense LTE-A networks [66, 19]
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Relevant Literature The paper entitled ‘Towards efficient mobile M2M communications: Survey and open challenges’ [11] provided insights into reference architectures for M2M with a focus on European Telecommunications Standards Institute (ETSI) network architecture. A major contribution of this work is its exploration of the use of smartphones as gateways for M2M communication. Related research includes [20, 105, 106, 107]. [20] surveyed technologies and networking techniques for M2M communication with their associated limitations. Similarly, they discussed short-range capillary networks and application development protocols. [105] evaluated latency performance in IoT using mobile gateways. [106] studied a ‘D2D-based IoT data collection’ scheme. In this approach, an IoT device aggregates data collected from smart objects (using D2D links) towards the eNodeB by using a Modulation and Coding Scheme (MCS). Motivated by the use of satellites to cater to a fraction of the M2M/IoT data, [107] proposed a congestion control mechanism in the random-access satellite channel which can be configured at the application layer. In the review paper entitled ‘Mobile M2M communication architectures, upcoming challenges, applications, and future directions’ [24], the authors discussed reference models, architectures, service requirements, standardisation efforts, applications, challenges and future directions related to mobile M2M. Some of the notable papers that have referred to this work include [108], which surveyed radio resource management for energy-efficiency in cellular networks, and [109], which presented a survey on networks and technologies for smart cities. Recently, [110] discussed current advances, architectures, and research challenges associated with M2M technologies.
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4.2. Vehicular M2M Autonomous vehicular communication is one of the key applications of M2M communication. Its applications are extensive and its implications are beyond current expectancies. Particularly, this technology can reduce transportation costs. For instance, driverless cabs are expected to make transportation more accessible to low-income households [111] who may not afford to own cars. Other applications include safety and collision avoidance, management of traffic and infrastructure, vehicle telematics, and in-car entertainment and internet services. Owing to the unique mobility patterns associated with vehicles as compared to cellular devices, vehicular networks are characterised by an architecture consisting of five major parts that include intra-car 22
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networks, vehicle-to-vehicle (V2V) networks, vehicle-to-infrastructure (V2I) networks, backhaul, and servers [23]. Sensors and car-instruments (e.g. airbag system) can collect data while Media Oriented Systems Transport (MOST) ring facilitates intra-car communication. An On-Board Unit (OBU) and the bus master on the MOST ring can aggregate data. Similarly, Wireless Access to Vehicular Environment (WAVE) can be deployed for intra-vehicle and extra-vehicle communication. Through the MOST ring, media can connect to infrastructures through wireless technologies with high bandwidth such as Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), and cellular networks for video, audio, or internet services. Road side units and access points for high-bandwidth technologies can function as gateways to Intelligent Transport System (ITS) and internet as backhaul services. Using the internet and ITS, vehicles can communicate with back-end servers [23]. In the pursuit of effective autonomous vehicular communication, it is important to ensure that involved entities in communication can be visualized. Devices should also be easy to control and the process of sending reports should be automated. A few other necessities include [23, 111]:
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• vehicular network autonomy that would help to achieve security, centralized management systems, and dynamic connectivity;
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• mechanisms that would address the challenges of V2V and V2I connectivity;
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• cross-platform networking for inter-vehicle and intra-vehicle communication;
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• adapting to the dynamic evolution and diversity of consumer electronic devices;
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• mechanisms that would discreetly accommodate the unpredictable movement of nodes that could hinder proper inter-vehicle communication; • preserving privacy of vehicular users such as traffic reporting; • mechanisms for efficient vehicle routing so that autonomous vehicles could easily determine appropriate routes in road networks; • addressing operational setbacks associated with the functionality of electric vehicles such as battery durability, size and lifetime. 23
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Relevant Literature In the article entitled ‘Machine-to-Machine Communication in Vehicular networks’, Booysen et al.[23] described the generic M2M architecture and the communication standards associated with vehicular networks such as Controller Area Network (CAN), MOST, WAVE, Wi-Fi, WiMAX, and cellular standards. This work has been referred to in [112, 113, 114, 115]. Reference [112] gave insights into vehicle electrification and intelligent transport systems for future smart grid networks considering the entities and components involved. They discussed electrified transportation with respect to societal adaptation and communication perspectives. [113] presented a survey on cooperative platoon-based driving with physical dynamics in Vehicular adhoc Networks (VANETs). [114] surveyed current approaches targeted at the deployment of smartphones to enhance ITS including the opportunities and challenges associated with smartphone-assisted driving. Reference [115] considered Internet of Vehicles (IoV) and proposed a framework for layered architecture to address relevant problems. In the article entitled ‘Autonomous vehicles: challenges, opportunities, and future implications for transportation policies’ [111], the authors discussed an array of issues including ethical challenges and opportunities associated with autonomous vehicles with respect to transport policies. They presented a navigation model for effective ‘traffic circulations’ in autonomous vehicular communication. The relationship and differences between machine-to-machine communication, wireless sensor networks, cyber physical systems, and Internet of things were considered in ‘Machine-to-Machine Communications: Architectures, Standards and Applications’ [13]. The potential of a cyber-transport system to enhance road safety was shown in the form of a novel system that brings together the concept of an unmanned vehicle using sensor navigation and an intelligent road to avoid intersection collision. Further research challenges were also identified. Works that have referred to this article include [116, 117, 118, 119, 120]. Reference [116] proposed an autonomous, secure, and economic M2M system for e-health. The proposed system also accommodates dynamic allocation of medical doctors. Reference [117] presented a 4-layered IoT architecture with an intelligent system based on Radio Frequency Identification (RFID) for M2M communication. Authors in reference [118] considered the priority scheduling approach deployable in applications requiring instantaneous
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5. Standards and Service Platforms
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response such as healthcare. Reference [119] presented event-driven architectures for M2M communication. [120] considered a framework for smart home applications, incorporating several previously proposed frameworks and architectures.
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One of the key constituents for the rapid development of M2M markets is standardisation activities [7]. This is quite challenging because of the wide range of M2M applications. Consequently, the scope of standardisation efforts becomes wider than other traditional networks [24]. Consequently, several standards development organisations are making efforts to facilitate M2M communication. Among these are 3GPP [121], ETSI [122], Internet Engineering Task Force (IETF) [123], oneM2M [124] and NB-IOT [125]. 3GPP provides a stable environment for members to produce reports and specifications that are used to define its technologies. Amongst others, the 3GPP technologies include radio access, core transport network, and service capabilities. 3GPP consists of seven member telecommunication standards development organisations [121]. ETSI is concerned with developing standards that are globally applicable for information communication technologies. These include fixed, mobile, broadcast, and radio and Internet technologies. It is a large body consisting of eight hundred member organisations from sixty-six countries and five continents [122]. The IETF is an international community involving several stakeholders such as network designers, vendors, operators, and researchers working towards the smooth operation of the Internet and the evolution of its architecture [123]. oneM2M is a global standard initiative targeted at M2M and IoT. To address the need for a uniform service layer that can be embedded in various hardware and software, oneM2M develops the required technical specifications. Furthermore, oneM2M is also concerned with the reliable connectivity of several devices with M2M servers all over the world [124]. NB-IoT is a new narrowband radio technology standardised by 3GPP and completed in 2016. It is aimed at addressing the requirements of IoT such as coverage, support for massive devices, low power consumption, low cost, and optimised network architecture [125].
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5.1. Standards’ Requirements Because multiple stakeholders are involved in M2M, it is essential that M2M systems should be based on open standards as their lifetime would be extended for over many years. In addition, standards must be rapidly developed for interoperability and global market and economies of scale support as needed by the industry. Standards should also support multiple classes of delay using an enforcement delay mechanism for the development of M2M/IoT applications. This can be done by leveraging the pros of standards such as Differentiated Services (DiffServ) and Integrated services (IntServ) for QoS requirements. For applications such as smart home, semantics and relevant data are required in the abstraction of such M2M use-cases. The use of information semantics would also cater to the need of providing common enablers to M2M applications for discovery, interpretation, and utilisation of data from different sources [25]. Several open issues associated with standards include [25] and [6, 10, 27, 32]: • the need for working on adequate device management (on a large scale) and remote software management;
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• the need for handling the complexity associated with device identification of technological specifications. This would help to improve the market potential of M2M; • the need for bringing computing facilities closer to data to address the concern of transferring data to computing facilities;
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• the need for organisations to convert large amounts of incoming data to a standard format in current M2M deployments to facilitate proper data analysis;
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Relevant Literature In the paper entitled ‘M2M Communications for E-Health and Smart Grid: An Industry and Standard Perspective’, Fan et al.[10] discussed M2M standardisation activities analysing their enabling technologies and industrial applications. Smart grid and e-health were discussed as typical examples of
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M2M applications with a summary of ongoing industrial and standardisation efforts. The discussion entailed academic perspectives published in the literature and how they are augmented. Reference [10] has been referred to in [126, 127, 128]. [126] discussed meta-architectures for harmonising standardisation technologies, including architecture and protocol interoperation for smart grids. [127] surveyed 5G mobile networks while [128] surveyed challenges for M2M in smart grids. In ‘A survey of standards for Machine-to-Machine and Internet of Things’, Gazis [25] reviewed major challenges of future standardisation in IoT. The features of several standards and architectures were summarised and classified under different headings such as progress/release state, internet protocol stack layer, and deployment perspective/coordination model. Classification was based on supported domains, architectural styles, and contributed definitive elements. Amongst others, this work has been referred to in [129, 130, 131]. [129] surveyed real-time analytics and other proposed network methodologies for IoT. Reference [130] estimated the quality of transmission and spatial frequency reuse and optimised massive IoT systems. [131] considered security standardisation for IoT. The article ‘Machine-to-Machine (M2M) communications: A survey’ [7] presented a generic system model for the device, network, and application domains of M2M. Several system models and architectures proposed by different standards developing organisations such as 3GPP, ETSI, and oneM2M were also discussed. A characterisation of M2M data traffic was performed by various standardisation bodies and their specific tasks. This work has been referred to in papers such as [132, 133, 134, 135]. Reference [132] studied the clustering algorithm for MTC over LTE for data processing by considering mobility. Authors in [133] studied localisation problems among ‘blind’ machine devices in ‘noisy’ environments. [134] considered the deployment of M2M communication to enhance fault-detection accuracy in industrial applications. Reference [135] considered an analytical approach for medium access control to investigate the performance of M2M and D2D communication with unlicensed resources. 5.2. Service Platforms To ensure interoperability, ease of discovery, and proper management, M2M systems should be managed with an appropriate level of abstraction. In this manner, devices can be organised to collaborate and share complex 27
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information. The platforms on which the devices are managed can be referred to as M2M service platforms [136]. As discussed by Kim et al. [26], M2M platform models can be classified based on commercialisation and research. The first class of M2M platform models include a customer-to-customer and business-to-customer model that would be beneficial to individual users with a limited number of different devices. Devices can periodically send data to subscribers based on events. Objects can also be collected from sensors, which can be retrieved from the access gateway. The second class of M2M platform models are research-based, which accommodates both authorised personal user devices and public devices. Smart object resources are shared through virtualisation and can be searched and discovered. These platforms are not devoid of requirements vital for successful application. In the industrial domain, major players associated with service platforms have to establish an ‘ecosystem’ that would reduce the cost of development and the time to market M2M devices. The service platforms must also be supported by enabling technologies and standardisations. This would help bring down development cost, reduce the time to market M2M services, and achieve service-convergence among industries through data sharing. Other requirements are given below [26]:
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• Internet-connected objects must be registered to platforms where they can be authenticated, searched, and modified; • Platforms should have the ability to autonomously control and instruct devices and actuators in reaction to collected data;
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• Apart from managing individual devices, functionality should also be supported by the platform;
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• Smart devices should be capable of accessing services using an application or the web. The app store can be managed by the platforms;
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• Platforms offering cloud services should be able to store data from sensors and objects; • Interoperation and mutual connection of M2M devices should also be supported; • Platforms should have the capability of being accessed via the internet at any time and from any location; 28
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• Platforms should have the ability to provide peer-to-peer (P2P) communication support;
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• It is also necessary to develop an M2M platform to realise the future conception of M2M services.
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A typical service platform architecture such as M2M Service Platform (M2SP) [26] can include an M2M area network, access network, and a CN. The M2M area network consists of heterogeneous networks with a sink that connects the network through access networks. The CN accommodates various traffic types from several objects and provides reliability and QoS guarantees for such traffic. Users and objects connected to the CN are managed and M2SP provides services. A typical scenario that illustrates the manner in which different components and stakeholders interact is a vending machine. In this case, a user can find the location of a vending machine with a specific product. The service provider manages the stock of vending machines and provides product details and advertisements. Some issues and future considerations for service platforms are given below [26, 27]: • Processing management information in bulk can reduce network performance degradation because of dead nodes.
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• Enabling virtualisation of M2M communication. • Developing solutions to realise autonomic service networks.
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• Considering P2P communication to reduce delay and efficiently handle unnecessary traffic. However, for massive M2M, a signalling process for authorization between devices and resource allocation is required.
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Relevant Literature In the article [26] entitled ‘M2M Service platforms; survey, issues, enabling technologies’, a service platform architecture with a sample service scenario was proposed. Several application use-cases were provided to demonstrate the way components of this platform interacted. The authors further discussed standardisation activities in international standards organisations (ISO) and provided future research directions. Some works that have referred to this paper include [137, 138, 139, 140]. [137] thoroughly studied 5G wireless evolution, [138] considered pricing models in 29
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Wireless Sensor Networks (WSN), M2M and IoT while [139] reviewed RA procedures and probable solutions for satellite networks. [140] deployed use cases consisting of several platforms to evaluate inter-networking interfaces using oneM2M. The authors of ‘Machine-type communications: Current status and future perspectives of 5G systems’ [28] ‘mapped’ MTC requirements and their likely solutions. They provided a picture of current cellular technologies progressing towards MTC in 5G mobile systems. Similarly, the service functions, requirements, applications, and corresponding issues were discussed. This paper has been referred to in [141, 142, 143, 144]. Authors in [141] surveyed security threats and solutions in MTC and further presented an authentication scheme for scalable LTE heterogeneous networks. [142] presented a dynamic resource allocation mechanism using learning automaton (LA) to assign resources to devices based on their priorities. [143] surveyed notable advancements in technology for 5G wireless communication including issues and possible solutions. Authors in [144] surveyed unmanned aerial vehicles (UAVs) using MTC for IoT.
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The LTE technology is growing rapidly [145] and is being enhanced to support new applications and technologies in recent years. LTE-A is an enhanced version of the LTE cellular network [146]. The LTE/LTE-A network is of particular interest as it can cope with the increased usage of mobile data and multimedia applications [147]. Next, we briefly introduce the LTEA architecture which supports M2M communication and highlight some of its challenges.
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6.1. Network Architecture As shown in Fig. 7, an LTE network consists of the Evolved Packet Core (EPC) and the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). The E-UTRAN comprises of eNBs that are connected to each other by the X2 interface. The S1 interface connects each eNB to the EPC. The serving gateway (S-GW) is terminated by the S1 interface on the user plane, while on the signalling plane, the S1 interface terminates the Mobility Management Entity (MME). To enable M2M communication, machine devices can connect to the eNB directly or through a gateway. Services are
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Figure 7: A basic LTE/LTE-A architecture with M2M communication
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provided by MTC servers that can be accessed by the users in the application domain [92]. Machine devices can also connect to each other in a P2P fashion. Cellular M2M networks play a key role in wireless infrastructure. A flexible network architecture is required, keeping in view the present and future technologies. Because it is necessary to centrally locate data obtained from M2M devices, a cloud-based solution will be highly propitious and would help achieve cost efficiency, scalability, continuous availability, and accessibility [4, 7]. 3GPP has made provisions to accommodate MTC at the physical layer of the LTE architecture [148]. 3GPP LTE and LTE-A have several advantages over other access technologies because they have a flexible radio resource management scheme. However, they were not envisioned for applications characterised by small amounts of data like M2M applications. They are used for wideband applications. The consequence of this is an inefficient utilisation of technology [29]. As such, there is a need for a standard end-to-end architecture to integrate 31
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network solutions from different MTC stakeholders. This would help to give reliable interconnectivity between devices all over the globe. Constructing and managing connections among several MTC devices distributed over a vast area has several challenges. For instance, in the case of an air interface (i.e. the radio-frequency-based connection/communication medium between the mobile base station and user equipment [149, 150]), there are challenges associated with the use of current H2H mechanisms for M2M communication. The challenges include PHY transmission issues, RA procedure issues, energy and complexity challenges, and radio resource allocation for critical QoS provision [6]. Another major problem in MTC cellular networks is congestion due to simultaneous signalling messages from machine devices, possibly resulting in peak load situations [151]. This negatively affects mobile network operation and performance of critical nodes with limited resources. To address this problem, a bulk signalling handling approach can be used [9]. Using this scheme, similar signalling messages from MTC are handled in bulk. This approach can be used as a complementary or alternative method of controlling network congestion and overload in M2M. Extending network coding and random data combination is required for reliability and error control in heterogeneous M2M communication in 3GPP LTE/LTE-A. The network coding provides an effective means to achieve efficient and reliable transfer of data. It also requires very little coordination among nodes. Distributed processing paradigms can also be considered for decoding in dense M2M networks. In addition, ensuring efficient and timely analysis of data gathered by M2M devices can be achieved using various machine learning techniques. However, it should be noted that this requirement depends on the application. Other challenges associated with M2M network architecture include [6, 9, 29]: • ensuring connectivity, compatibility, and interoperability within M2M communication network;
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and M2M devices through more Evolved Universal Terrestrial Radio Access (E-UTRA); • characterising M2M traffic to handle several QoS requirements;
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• developing more reliable transmission mechanisms;
• considering unsophisticated, fixed, and conservative techniques for the design of link adaptation;
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• determining whether additional resources shall be allocated for the Physical Downlink Control Channel (PDCCH) and whether the PDCCH shall be separated for MTC devices and UEs.
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Relevant Literature The article entitled ‘Machine Type Communications in 3GPP Networks: Potential, Challenges, and Solutions’ [9] focused on 3GPP Release 10. The authors proposed a bulk signalling handling approach for congestion control and network overload avoidance. [9] has been referenced in [152, 153, 154, 155].Reference [152] examined mobile telecommunication trends, issues, and the possibility of bringing the cloud service to mobile users. [153] presented enhancements for M2M and IoT in 3GPP concerning architecture, management, monitoring, power, and latency. [154] studied the significance of multihop-based D2D communication in extending M2M network coverage and range. Authors in [155] focused on physical control channel issues for LTE-based M2M communication with a proposed solution for handling physical limitations associated with M2M devices. In the survey entitled ‘M2M Communications in 3GPP LTE/LTE-A Networks: Architectures, service requirements, challenges and applications’,[29] presented enhancements concerning LTE/LTE-A architecture in M2M networks and examined challenges of M2M over 3GPP, LTE/LTE-A. This work has been referenced in a number of research papers including [156, 157, 158]. The authors in [156] focused on using a dynamic grouping approach controlled by the gateway to reduce signalling overhead in MTC over LTE. Authors in [157] proposed an approach to determine the required number of preambles to achieve maximum throughput for an unknown number of devices and access probability. Recently, [158] presented a detailed survey on cognitive radio for machine-to-machine communications. In this respect the
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authors discussed challenges and benefits associated with the amalgamation of these technologies. Lien et. al [6] presented an overview of M2M features and network architectures in 3GPP and LTE-A in the survey entitled ‘Towards Ubiquitous Massive Accesses in 3GPP Machine-to-Machine Communications’. The challenges related to an air interface of LTE-A were examined. An effective grouping-based radio resource management was proposed to facilitate M2M applications with strict timing constraints for QoS guarantees. This survey has been referenced in articles such as [159, 151, 160, 161, 162, 163, 164, 165]. [159] studied RACH overload and key challenges in LTE-A. [151] addressed the congestion issue in MTC using congestion-aware admission control. [162] proposed a dynamic overload control algorithm to resolve congestion at the RAN because of massive M2M device requests. Reference [163] put forward a group model based on MTD traffic to achieve efficient resource management for MTC. [164] proposed an RACH for 5G MTDs that transmit small packets within the RA burst. This allows machine device detection, decoding, channel estimation, and security authentication. Recently, [165] analysed a new Millimeter wave-non-orthogonal multiple access transmission mechanism for achieving QoS guarantees in cellular M2M. The authors also proposed an BSto-MTD distance-based device pairing schemes to cut overhead and latency in cellular M2M networks.
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6.2. Ultra-dense Networks One of the main technologies that would enable future wireless communication is Ultra-Dense Networks (UDNs) [30]. UDNs have several unique features that set them apart from traditional cellular networks. First, the number of communication links and (or) access nodes are densified for each unit of area. In other words, there are many small cells in the vicinity of each user. This would mean that several of these small cells would also be inactive. From the above description, an increase in the density of small cells would mean a high level of interference. In addition, very innovative approaches for handling frequency reuse would be required. Another feature of UDNs is that line-of-sight (LOS) communication would be higher. However, achieving low-delay and high-speed backhaul would pose challenges to network designers [166]. Because M2M communication will become a vital component of future 5G wireless networks consisting of UDNs, there is a need for comprehensive studies on M2M in UDNs. Application scenarios of M2M in UDNs include 34
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apartments, industries, enterprises, and hotspots. Although, cellular networks inherently include UDNs, implementing M2M communication poses peculiar challenges at different layers of the protocol stack [30]. In relation to the PHY layer, supporting multiple non-cellular technologies is a challenge especially in Small cell Base Station (SBS)-based or distributed antenna system (DAS)-based UDNs. In other words, cellular and non-cellular interfaces should be accommodated by either machine-type gateways or Small cell Base Station/Radio Remote Head (SBS/RRU). However, a different design of SBS/RRU is required for other configurations. An advantage of this approach is that the expense of deploying machine-type gateways will not be an issue of concern [30]. In relation to the MAC layer, four major challenges must be considered for implementing M2M communication in UDNs: • Concurrent access of machine devices;
• Resource allocation efficiency because H2H and M2M would co-exist within the network.
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• Appropriate selection of RATs for machine devices.
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In the network layer, finding an appropriate routing mechanism is the most paramount concern. This can be achieved in several ways using machine-type gateways or UEs as relay nodes between machine devices and the CN. Similarly, the BS could also be used for data relay. The application layer requires improvements to ensure that resources are not wasted because of M2M communication. In this regard, the waiting time of machine-type devices can be made dependent on latency requirements. It is necessary to design protocols that efficiently accommodate the unique characteristics of M2M traffic [30]. In the physical and medium access layers, some modifications or enhancements might be necessary. The main research questions related to the implementation of M2M communication in UDNs are as follows [30]: • Supporting non-cellular M2M networks in UDNs; • Improving transmission efficiency for M2M in UDNs; • Minimising the number of required active gateways for M2M in UDNs; 35
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• Designing priority-based resource allocation mechanisms for machinetype and H2H communication; • Efficient separation of M2M and H2H traffic at base stations;
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• Efficient coordination among BS by grouping or clustering the BSs; • Defining new service categories for several M2M applications.
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Another promising direction in UDNs is highly efficient device positioning for location-aware applications. Specifically, robots, drones, and vehicles can be accurately tracked for use in factories, intelligent transport systems, and autonomous cars [167]. This is propitious for several M2M applications.
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Relevant Literature In the article entitled ‘Machine-to-Machine Communication in UltraDense Networks: A Survey’ Chen et al., [30] married M2M and UDNs that have usually been separately considered in the literature. To support M2M in UDNs, they explored several service categories for small data transmission. Some papers that have referred to this work include [168], which achieved optimal throughput and scalability in ultra-dense multi-cell RA scenarios using a decentralised approach to transmission suited for machine communications. [169] proposed a security-aware mobile relay selection algorithm for M2M devices using multiple UEs. The relay perform aggregates and transmits data to the BS.
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7. Energy Efficiency, Reliability and Security
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The growth of M2M communication rests on understanding and managing the challenges of M2M. Among these challenges are energy-efficiency, reliability, and security (GRS) [2]. This section discusses issues related to energy-efficiency and reliable and secure M2M communication. Specifically, subsection 7.1 and 7.2 highlight issues related to energy-efficiency and reliability, respectively. In subsection 7.3, we present an overview of security issues with respect to M2M communication. We excluded technical details because of space considerations.
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7.1. Energy Efficiency In the context of wireless networks and mobile devices, one of the objectives of achieving energy-efficiency is to increase the battery life of devices. Specifically, energy-efficient communication is motivated by reducing the impact of C02 emission and to counter-balance the increasing cost of energy sustained by network operators [170]. Energy efficiency is crucial to the success of M2M communication. Many of the M2M applications require devices to operate for a long period of time with constraints in terms of computation power and battery life. Whenever M2M performs monitoring functions, data redundancy and energy loss can occur, which negatively affect the network lifetime. Therefore, for M2M networks to perform effectively, energyefficiency must be the focus of consideration. This is also important for environmental protection [31]. Energy efficiency can be realised in several domains using radio optimisation, data reduction, sleep/wakeup schemes, battery repletion, and architectural and proprietary energy saving methods. The reduction of energy loss can be achieved through several approaches. For instance, energy efficiency of monitoring devices can be improved by regulating their active modes [31]. Other insights into energy-efficiency actualisation and power optimisation include [7, 31, 171]:
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• Investigating the required number of hops for efficient communication with the cellular backbone;
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• Harvesting energy from natural sources (such as temperature, light, and mechanical sources);
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Relevant Literature In the article entitled ‘Energy efficient techniques for M2M communication: A survey’ [31], the authors classified energy-efficient techniques with respect to the optimisation of radio, reduction of data, sleep/wakeup schemes, battery repletion, architectural and proprietary techniques for energy saving in M2M. They compared and analysed energy efficient algorithms. A key feature of this paper is the classification of energy-efficient techniques based on the OSI model using equations and algorithms. Although, several papers were properly grouped into sections, they were not criticised. Apart from several papers, this study has been referred to in [172] and [173]. Reference [172] surveyed current research issues in M2M, specifically in smart grid scenarios. The authors also presented M2M standards advancements and the potential of cognitive radio for big data communication. [173] investigated clustering approaches for enhancing the lifetime and connectivity of M2M networks with sink mobility (for load balancing). Energy-efficient shortest-path routing (SPR) based networking mechanisms were comprehensively reviewed in the paper entitled ‘Energy efficient wireless unicast routing alternatives for machine-to-machine networks’ [32]. Energy-efficient unicast routing alternatives for sensor and adhoc networks were classified with a focus on additive link cost-based alternatives. However, the survey did not consider information collection-based (sensing) type of energy consumption [32]. Similarly, many of the routing techniques surveyed were designed for stationary nodes. Further survey can focus on scalability [32], protocol designs for mobile nodes, and topology dynamics. This work has been referenced in [31], which we reviewed in this paper, and [174] presented power efficient schemes for mobile adhoc network (MANET).
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7.2. Reliability Reliability refers to the timely and effective transport of the required data for its target applications. In other words, it defines the quantity of sent packets that ought to reach its destination within the required delay bound [175]. It is essential to mention that, the amount of data required to ensure reliability is application dependent. In traditional sensor networks, this could be achieved either by packet re-transmissions or recovering lost bits within a packet using coding schemes. Retransmissions result in additional overhead due to transmissions. This could cause network congestion and waste energy of sensors with constrained energy resources. The second approach achieves
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reliability and reduces transmission overhead since lost or corrupted bits within a packet are corrected [176]. Without assurances of reliability, concerned entities may be disinterested in the potential of M2M communication. Reliability is pivotal to achieving green M2M because misleading reports, prolonged delays, and data loss can occur because of inaccurate sensing, processing, and transmission [2]. For example, in applications very sensitive to latency such as alarms for intruder detection, if the alarm response is not timely, the intruder might leave the vicinity of the event unnoticed. Structural health monitoring requires long-term functional networks. In such applications, energy-aware routing algorithms, which consider residual energy levels for maximising network lifetime, are necessary [32]. For some critical monitoring applications, packet retransmissions may severely decrease network lifetime, and therefore, retransmission-aware energyefficient routing algorithms can be advantageous [32]. Reliability can be improved by exploiting redundant technologies such as information and spatial and temporal redundancy. Although, redundancy is an effective solution, it comes with additional cost [2]. In industrial automation systems where a hybrid of wired and wireless architecture may be required, achieving the target reliability may pose challenges. This can be approached using QoS aware schedulers. For instance, the solution proposed in [175] can be adapted to suit M2M applications with diverse delay bounds in these environments. Balancing energy-efficiency and reliability remains an open issue in M2M communication.
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Relevant Literature Lu et al. [2] presented major technical requirements for emerging M2M communication in the article entitled ‘GRS: The Green, Reliability, and Security of Emerging Machine-to-Machine Communications’. A scheme for energy efficiency in M2M communication was provided with a discussion on several alternatives for ensuring high-level reliability and security. However, GRS issues were only discussed in a general context. According to the authors, it is necessary to identify and address GRS issues for several existing and upcoming M2M applications. A few notable papers that have referred to this work include [7, 11, 22], which we have considered in this survey and [177, 178, 23, 179, 181]. Reference [177] proposed an aggregation scheme for preserving privacy in smart grids while [178] addressed security concerns for 5G using a lightweight 39
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message authentication scheme. [23] concentrated on M2M communication in vehicular networks, [179] extended Fog computing3 for distributed decentralised smart building management, identifying issues yet to be studied. [181] presented technologies, challenges, and foresights concerning energyefficient IoT.
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7.3. Security Network security refers to the mechanisms put in place to ensure confidential, undefiled and trustworthy transfer of information. As such, there should be an assurance of confidentiality, integrity and non-repudiation of data transfer within the network [182]. Security issues can hinder the growth of M2M and some of its applications as considerable personal data can be ‘stolen’ from M2M devices when compared to personal communication devices. M2M is also characterised by existing threats in data communication. These threats can be classified as physical, logical, and data attacks. Physical attacks include theft, modification of software, and side-channel attacks. Logical attacks include impersonation, denial of service [183], and relay attacks [27]. Data attacks include privacy, data alteration, and selecting forwarding attacks. M2M security concerns also include trust creation, advanced credential management for mobile communication, and horizontal end-to-end security solutions [27]. In cellular networks, M2M deployed in UDNs poses security concerns such as privacy issues. Such issues are attributable to the heterogeneous network structure and the ‘frequent’ handovers that exist in such networks. Security should be considered from the outset of M2M application development in a holistic manner as general requirements may differ from application-specific requirements. An example is the difference between telemetry-based e-Health body area networks and home area networks in terms of battery life and the number of devices [10]. Another important consideration is interoperability because the network generally consists of several protocols and heterogeneous capacity. Schemes using dynamic configuration and adaptive protocols for end-to-end security can be deployed to address this issue. M2M data must be secured from source to destination using hop by hop or end-to-end security [27]. Other considerations include [33]: 3
The Fog extends the Cloud by bringing it closer to the devices which produces data. This minimizes latency and retains sensitive data within the network [180].
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• Addressing issues related to mobility and delay-sensitivity. Proposed schemes should be robust to ensure that M2M communication is resilient against attacks;
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• Designing secure and scalable key management schemes;
• Ensuring mobility in security schemes for data origin authentication;
• Proposing robust lightweight and highly efficient cryptographic mechanisms;
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• Addressing entity authentication with minimal computation for devices having limited resources;
• Ensuring that privacy-preserving schemes consider the trade-off between delay, robustness, and resource constraints; • Addressing security issues associated with availability and group key management for multicast communication.
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Generally, M2M security schemes should effectively support authentication, proper identification of entities, confidentiality, data integrity, access control, and non-repudiation [34].
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Relevant Literature Latvakoski et al. [27] presented a review of M2M information and services in the paper ‘A Survey on M2M Service Networks’. The focus of this paper is on communication, security, and service technologies for M2M. The authors evaluated the effectiveness of technologies for addressing M2M service network issues. Reference [27] reviewed several security technologies related to Local Area Network (LAN) device domain. This article is referenced in [184], which surveyed the pros and cons of wireless technologies in home networks. The survey on M2M security entitled ‘M2M Security: Challenges and Solutions’ focused on critical issues for achieving secured M2M communication and preventing relevant attacks. The outstanding feature of this paper is that general M2M challenges such as scalability, heterogeneity, and resource constraints were discussed in the context of lapses in security. Future works should consider the issue of physical attacks as this paper mainly focused on logical and data attacks. Articles that have referred to this work include [185, 186, 187]. 41
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8. Conclusion
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Authors in [185] proposed a novel key management security protocol. This is was done to achieve maximal airtime savings in modern devices by using implicit certificates and Deffie-Hellman exchange. Reference [186] studied the effectiveness of current protocols and network stacks for IoT security. [187] proposed a scheme that recommends services for users of connected objects. Tuna et al. [34] surveyed security threats and potential solutions to minimise the impact of such threats or to mitigate the threats in M2M networks. This was presented in ‘A survey on information security threats and solutions for machine to machine (M2M) communications’. Consequently, the authors identified further research opportunities and challenges. There have been several recent references to Tuna et.al, including [188, 189]. Authors in [188] used the principles of blockchain technology to design a sophisticated blockchain structure for M2M communication based on a case study involving cotton spinning production for demonstration and validation. [189] proposed an authentication scheme suitable for multi-domain M2M scenarios. In addition to its authentication property, the scheme achieves anonymity by using a hybrid of certificateless cryptography and advanced encryption standards. It was shown to be effective against several security attacks such as Denial of service, impersonation, and replay and man-in-themiddle attacks.
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M2M communication has become a promising communication paradigm that would impact human lives in the years to come. This is because machine devices would communicate autonomously, thereby rendering interesting services to humans. Efforts are being made in academia and industry to ensure that the large number of machines involved in autonomous communication are well supported from several domains and there have been numerous articles on this matter. In this survey, we approached open questions in a particular way by classifying prime references in this area into themes and then discussing their fundamental concepts. Then potential areas for future work (some of which are summarized in Figure 8) were highlighted based on each theme. This is intended to present an overview of research opportunities available in these aspects. Relevant references for understanding such issues in greater depth were also reviewed with insights into their significant contributions and (or) limitations. More research and surveys that have spurred from these refer42
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Figure 8: Summary of some issues highlighted
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ences are highlighted with the aim of familiarising readers with some of the recent developments. Specifically, in this paper, we learn that one of the most crucial aspects of M2M communication is supporting the large number of machine devices with their diverse QoS requirements at the MAC layer. Other aspects include the proper choice of technology to support these devices and ensuring interoperability in terms of standards, service platforms, and architecture. It is important to cite that proper support for mobility, network densification, and gateways with cognitive capabilities is desirable. Reliable and secure solutions should be incorporated into the architecture of M2M while also considering energy efficiency. Looking into recent trends in wireless communication literature [137, 190, 191, 192, 193, 194, 195, 196, 197], it can be observed that advances in transportation, health, agriculture, manufacturing, and industry will present new challenges and further research opportunities for M2M communication. The ubiquitous use of autonomous vehicular communication is set to revolutionise the current transportation systems. Manufacturing will require more automated interactions of machines with the physical environment i.e cyberphysical systems. Critical health applications would require ultra-low latency M2M communication with ultra-reliable device connections. Smart drones and autonomous farm machines will also be able to work on large plots of land thereby reducing human effort. To realise these level of reliability and automation, several new technologies are expected to permeate the development of M2M communication. These include: edge computing, fog computing, and network slicing. Through edge computing, computational devices are brought closer to machine devices which would help mitigate traffic congestion, reduce latency in data exchange, improve the response time in real-time applications and improve the battery life of energy-constrained machine devices. Fog computing would enable machine devices to connect to fog clusters thereby facilitating proximity based M2M applications. Network slicing allows a physical infrastructure to accommodate several network instances in form of a virtual network architecture which is highly propitious for ultra-reliable and low-latency M2M communication. In the lower layer, network-coded multiple access (NCMA)4 and universal 4
a non-orthogonal multiple access scheme which uses non-orthogonal codewords for
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filtered multi-carrier (UFMC)5 are suitable for future advancement in M2M communication. NCMA is suitable for massive number of machines having small packets of data to transmit. This has the potential of improving the throughput, connectivity and, performance of M2M networks. Furthermore, it can reduce collision probability in contention based multiple access. UFMC is suitable for applications with short-bursts of traffic. Autonomous relay-assisted UAV communication, where UAVs can connect to terrestrial networks through relays, are also expected to find promising applications in the future. Asides the aforementioned, it is reasonable to expect that advances in M2M communication will also be driven by 6G expectations [199]. This would require advancements in technologies such as wireless charging and energy-harvesting. Current research [200, 201, 202, 203, 204, 205, 206, 207, 208] also shows that NB-IoT would highly impact M2M research in years to come thereby providing further opportunities. Acknowledgements
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The authors would like to appreciate everyone who gave comments and provided support to improve the content, quality and presentation of this paper. This work has been supported by the Malaysian Ministry of Higher Education under the Malaysian International Scholarship scheme. This publication is also supported by the Malaysian Ministry of Education under Research Management Center, Universiti Putra Malaysia, PUTRA Grant with High Impact UPM/700-2/1/GPB/2017/9557900.
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Table 1: Some key abbreviations used in this paper
Abbreviation
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3GPP 5G ACB BS CAN CN
Meaning 3rd Generation Partnership Project 5th Generation wireless systems Access Class Barring Base Station Controller Area Network Core Network
resource spreading [195, 198] 5 an alternative to orthogonal frequency division multiplexing [196]
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Table 1: Key Abbreviations (continued)
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Cyber Physical Systems Cognitive Radio Networks Device-to-Device Distributed Antenna System Distributed Queuing Evolved Node B Evolved Packet Core Evolved Universal Terrestrial Radio Access European Telecommunications Standards Institute General Packet Radio Service Global System for Mobile Communications Human-to-Human Internet of Things Internet of Vehicles Intelligent Transport System Local Area Network Low Power Wide Area Long-Term Evolution Long-Term Evolution Advanced LTE in unlicensed spectrum Medium Access Control Machine-to-Machine Multiple-input and Multiple-output Message Queueing Telemetry Transport Machine Type Communication Machine Type Devices On Board Unit Open Geospatial Consortium Peer-to-Peer Physical layer Physical Resource Blocks Physical Random Access Channel Quality of Service Random Access
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CPS CRNs D2D DAS DQ eNB EPC E-UTRA ETSI GPRS GSM H2H IoT IoV ITS LAN LPWA LTE LTE-A LTE-U MAC M2M MIMO MQTT MTC MTD OBU OGC P2P PHY PRBs PRACH QoS RA
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Table 1: Key Abbreviations (continued)
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Random Access Channel Radio Access Network Radio Access Technology Radio Frequency Identification Radio Remote Head Serving Gateway Small cell Base Station Service Capability Layer Standard Development Organisation Smart Utility Networks Sensor Web Enablement Time Division Multiple Access Ultra Dense Networks User Equipment Ultra-Wide Band Vehicular Adhoc Networks Vehicle-to-Vehicle Vehicle-to-Infrastructure Wireless Access to Vehicular Environment Wireless Fidelity Wireless Local Area Networks Wireless Sensor Networks
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RACH RAN RAT RFID RRU S-GW SBS SCL SDO SUNs SWE TDMA UDNs UE UWB VANET V2V V2I WAVE Wi-Fi WLAN WSN References
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Biography
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Oluwatosin Ahmed Amodu received his Bachelor of Technology degree in Electrical Electronics Engineering from the Federal University of Technology Akure, Nigeria 2012. He completed his Masters degree in Computer Science with a specialization in distributed computing at Universiti Putra Malaysia 2016. He is currently pursuing a PhD Programme in Wireless Communication and Network Engineering. His research interest lie in sensor networks, machine type communications, device-to-device communication, spectrum sharing networks and stochastic geometry.
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Mohamed Othman received the Ph.D. degree (Hons.) from the National University of Malaysia. He is currently a Professor in computer science with the Department of Communication Technology and Network, Universiti Putra Malaysia (UPM). Prior to that he was a Deputy Director of the Information Development and Communication Center, where he was in charge of UMPNet network campus, uSport Wireless Communication Project, and 72
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the UPM DataCenter. He is also an Associate Researcher and a Coordinator of high speed machine with the Laboratory of Computational Science and Informatics, Institute of Mathematical Science, UPM. In 2017, he received an Honorable Professor from South Kazakhstan Pedagogical University, Shymkent, Kazakhstan, and also was a Visiting Professor with South Kazakhstan State University, Shymkent, and L. N. Gumilyov Eurasian National University, Astana, Kazakhstan. He published more than 300 International journals and 330 proceeding papers. His main research interests are in the fields of computer networks, parallel and distributed computing, highspeed interconnection networks, network design and management (network security, wireless and traffic monitoring), consensus in IoT, and mathematical model in scientific computing. He is a member of the IEEE Computer Society, the IEEE Communication Society, Malaysian National Computer Confederation, and Malaysian Mathematical Society. He was a recipient of the Best Ph.D. Thesis in 2000 by Sime Darby Malaysia and Malaysian Mathematical Science Society. He has also filed six Malaysian, one Japanese, one South Korean, and three U.S. patents.
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Machine-to-Machine Communication: An Overview of Opportunities Oluwatosin Ahmed Amodu, Mohamed Othman PII: DOI: Reference:
S1389-1286(18)30851-X https://doi.org/10.1016/j.comnet.2018.09.001 COMPNW 6583
To appear in:
Computer Networks
Received date: Revised date: Accepted date:
21 February 2018 6 August 2018 2 September 2018
Please cite this article as: Oluwatosin Ahmed Amodu, Mohamed Othman, Machine-toMachine Communication: An Overview of Opportunities, Computer Networks (2018), doi: https://doi.org/10.1016/j.comnet.2018.09.001
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Machine-to-Machine Communication: An Overview of Opportunities
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Oluwatosin Ahmed Amodu∗, Mohamed Othman
Department of Communication Technology and Network, Universiti Putra Malaysia, 43400 UPM, Serdang, Selangor Darul Ehsan, Malaysia.
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Abstract
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The envisioned capability of machine devices to autonomously communicate in the future Internet of Things (IoT) has brought considerable attention to machine-to-machine (M2M) communication in recent years. This paradigm has applications in homes, safety, transport, health, and industry. As an active focus of research, there are interesting open questions on several of its aspects, which we aim to capture in this paper. Accompanied by an attempted classification of existing surveys on M2M, we propose a followable exposition on the challenges and open research opportunities that embrace the diverse facets of M2M.
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Keywords: access problems, applications, challenges, home, mobile, open issues, standards, survey, taxonomy, technologies, M2M, MAC.
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1. Introduction
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Machine-to-Machine (M2M) communication is the autonomous interaction of a large number of machine devices to perform sensing, processing, and actuation activities without human intervention. These devices include meters in a smart grid, electronics and servers, and navigation sensors used for relaying information through a network. The main feature that sets M2M apart from other communication paradigms is the absence of human supervision [1, 2, 3, 4, 5]. The primary objective of M2M communication is to ∗
Corresponding author Email addresses: [email protected] (Oluwatosin Ahmed Amodu), [email protected]; [email protected] (Mohamed Othman)
Preprint submitted to Computer Networks
September 3, 2018
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• The emergent automation of machine devices
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enable communication among smart devices [6]. This fast-growing paradigm with billions of inter-connected machines used for various applications is imminent [7]. M2M has been a focus of extensive research in recent years because of several reasons. Some of the reasons and enablers of M2M include [5, 7, 8, 9, 10, 11]:
• The pervasiveness of high-speed internet access
• The declining cost of sensing and actuating devices
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• The cheap, ubiquitous connectivity of electronic gadgets • The utility and variety of M2M applications
• The projected impact of M2M communication on cellular network connections and the growth rate • The use of machine devices in locations unfrequented by humans
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• The potential of M2M communication in generating revenue for cellular operators
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M2M applications span across various fields such as health, monitoring, security, home, and city automation. To facilitate such autonomous communication, several challenges must be addressed in different areas. Among other reasons, these challenges emerge from the unique characteristics of M2M communication in different architectural domains and its diverse applications. In this paper, we present the challenges and opportunities associated with various aspects of M2M communication shown in Figure 1, which is based on the emphasis placed on such aspects in the existing literature (see Figure 2). We provide a high-level summary of relevant literature in each aspect, indicating some other related articles, to familiarise readers with other recent research. The organisation of the main sections of this paper (Sections 2 to 7) is shown in Figure 3. A more general approach to classifying M2M communication is to categorise it into cellular and capillary M2M communication as presented in [12]. However, our discussion in this paper emphasises the aspects of the research in the literature from different perspectives such as application use cases. 2
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Figure 1: Classification of themes for M2M communication
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It is worth noting that the classified aspects in this paper are not fully orthogonal because the objective is to emphasise the opportunities that are available based on a careful study of existing surveys in this field. For instance, Long-Term Evolution (LTE)/Long-Term Evolution-Advanced (LTEA) can be classified as a standard but we have included LTE/LTE-A as a separate section for emphasis. Furthermore, [7, 12, 13] could have assumed a more general classification but a key aspect in each survey was considered. Our findings demonstrate that as the number of existing surveys increase, it is essential to capture some of the key efforts that have been presented in such surveys. Therefore, we present Figures 4, 5 and 6. 3
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Figures 4 and 5 classify summary tables presented in these references, guiding the interested reader to associated references for subjects of interest. For example, a reader can find an ‘overview of contention-based channel access mechanisms in various communication technologies for IoT’ under medium access in Figure 5 in reference [14]. Similarly, Figure 6 guides readers to cardinal illustrations (such as architectures) in the literature. The remainder of this paper is organised as follows: Section 2 examines issues related to medium access of the M2M wireless channel. Section 3 discusses M2M architecture and technologies associated with home applications. Section 4 provides insights into M2M for mobile deployments, which includes the challenges, vehicular M2M architecture and related issues. Section 5 explores several standardisation efforts in M2M/IoT. Section 6 examines cellular LTE/LTE-A networks and ultra-dense networks (UDNs). Section 7 analyses issues concerning energy efficiency, reliability, and security in M2M with potential solutions. Section 8 concludes this paper. Common notations used in this paper are provided in Table 1 within the appendix.
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2. Medium Access
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As M2M is envisioned to involve millions of machine devices, it presents several challenges in research. One of the fundamental issues of critical concern is the inability of access management mechanisms in traditional wireless networks to accommodate the unprecedented number of projected devices while satisfying the necessary quality of service (QoS) requirements. In this section, we will discuss the fundamental issues pertaining to medium access protocols in traditional and cellular networks, including their pros and cons. Considerations for choosing or designing protocols and open issues will be discussed.
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2.1. MAC protocols for M2M Medium access control (MAC) schemes define the rules which allow devices to communicate with each other in an orderly and efficient manner [35]. The development of MAC protocols plays a vital role in the pursuit of autonomous machine communication. Generally, traditional MAC protocols can be broadly categorised into three classes, namely contentionbased, contention-free, and hybrid schemes. These three schemes differ in the approach by which transmission time slots are acquired and managed. In contention-based schemes, nodes contend for access to the shared medium. 4
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Figure 2: Taxonomy of survey papers for M2M communication
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Whenever any node acquires the channel, it transmits at a specific time slot. The node defers transmission if the channel is busy. If the state of the channel is empty, the node transmits or backs-off for a random time before it transmits [16]. Contention-free schemes, on the other hand, have pre-allocated time slots for each node to transmit. Hybrid schemes combine both contention-based and contention-free schemes. Contention-based schemes do not scale at high loads i.e. their performance degrades with an increase in the number of nodes. Contention-based schemes are also not energy-efficient as the retransmission of packets leads to energy loss. Another issue is that in contention-based schemes where nodes back-off because of contention, the back-off parameters are selected based on the traffic load. Clearly, this may not be efficient in applications where 5
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Introduction
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A primer to introduce each aspect
Discussion on key aspects
Main Section
Subsections
Future considerations
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Relevant Literature
Main references and other associated references
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Figure 3: Organisation of main sections in this paper
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delay-critical information must be shared for safety as in the case of sharing information between pedestrians, vehicles, and road infrastructure [14]. On the contrary, contention-free schemes are more energy efficient and possess better scalability. However, they cannot adapt to dynamic network conditions because node transmission occurs at scheduled time slots. Delay is also incurred since devices would have to wait for their assigned time slots. The use of hybrid schemes, which combine the advantages of the above approaches and offset the demerits, have also been considered in the wireless networks (adhoc and sensor network) literature [36] and recently for M2M [37, 38, 39]. In terms of the fraction of channel capacity deployed for data transmission i.e. throughput, hybrid schemes generally perform better than contention-based schemes (especially at high loads). However, hybrid schemes still incur longer delays as compared with contention-free schemes e.g. Time Division Multiple Access (TDMA) for lesser number of devices in [37, 38]. Tree-based schemes such as the distributed queuing (DQ) algorithm [41] where a group of contending devices are iteratively split to smaller subgroups 6
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to reduce collisions, have been studied and found suitable for M2M networks [40]. Specifically, the DQ algorithm achieves fairness and scalability for an unlimited number of devices [14, 15]. Recently, a hybrid collision avoidance tree-resolution mechanism was proposed in [42]. The scheme demonstrates better performance compared with collision avoidance mechanisms without the tree-based access. [43] proposed a hybrid of adaptive slotted-ALOHA and TDMA to achieve resource utilisation in LTE/LTE-A under strict fairness constraints. The authors [44] proposed a hybrid of slotted-CSMA and TDMA for massive IoT devices. The algorithm caters to an efficient registration of up to eight thousand devices when these devices attempt to register at one centralized access point. [45] combines contention and contention-free mechanisms to address preamble collision in LTE because of periodic machine access. A number of further directions associated with the MAC layer includes [8, 16]: • Handling scalability for massive machine device connections; • Designing MAC layer schedulers for M2M applications;
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• Incorporating low power communication into scalable MAC protocol design;
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• Supporting priority access for applications such as alarming applications by supporting differentiated bandwidth requests, resource reservation, admission control, and priority-based service pre-emption;
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• Devising support for diverse QoS requirements; • Deploying heterogeneous transceivers;
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• Designing MAC protocols that support multi-hop architectures; • Developing energy-harvesting aware MAC protocols;
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• Devising support for clustering at the MAC layer; • Supporting new technologies like wake-up radio; • Designing mobility-aware MAC protocols; • Devising support for intra-M2M connectivity at the MAC layer. 7
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Apart from the above issues related to the MAC layer, cross-layer optimisation should be intuitively enhanced in a manner that is independent of the production of new commercial hardware [7].
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Relevant Literature In the survey entitled ‘A Survey of MAC layer Issues and Protocols for Machine-to-Machine Communications’ [8], the authors highlighted the key characteristics of MAC protocols for M2M communication with a focus on ensuring scalable, efficient, and fair channel access for machine devices. They discussed MAC protocols specifically proposed for M2M communication. Limitations for [46, 47, 48] were highlighted; however, no critique was presented for [49, 50, 51]. Future work is required to extend the proposed taxonomy for medium access proposals with the inclusion of tree-based contention resolution, energy-harvesting protocols, and other recent proposals. Among others, this work has been referenced in [52, 53, 54, 55]. Authors in [52] presented a comprehensive survey of fog and cloud Radio Access Network (RAN) for 5th Generation wireless system (5G) networks; investigating a synergy of these two architectures for the diverse needs of 5G mobile networks. [53] designed a random access scheme for M2M data transmission in applications with delay constraints. The protocol inherits the benefits of DQ’s collision resolution as well as the efficiency of the data transmission in Multiple-input and Multiple-output (MIMO). Recently, [54] proposed an intelligent CSMA-based collision avoidance mechanism suitable for capillary M2M communication characterised by low power and short-range transmissions. [55] studied a multi-channel CSMA for M2M communication. They show that the traffic load defines the gains in energy efficiency and delay achieved when the frequency band is divided into sub-bands Laya et al. considered the MAC solutions for IoT in the article ‘Goodbye Aloha!’ [14]. They presented the DQ protocol, demonstrating that it works for an infinite number of machine devices regardless of the network load and traffic pattern. A major contribution is its invitation of the research community to consider an alternative to the current ALOHA-based protocols for deployment in IoT. This paper has been referred to in [56, 57, 58]. Reference [56] surveyed low power wide area (LPWA) networks and [57] reviewed LTE random access channel (RACH) for IoT, evaluating the performance of 3rd Generation Partnership Project (3GPP) schemes for overload control. Similarly, [58] addressed preamble collision for massive smart devices using the preamble grouping method. 8
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Recently, [16] presented ‘A survey of hybrid MAC protocols for machineto-machine communications’. The paper focused on peculiar areas pertaining to a recent trend in MAC protocol design for M2M by providing insights into the objectives and problems solved in different protocols while revealing enhancement opportunities and potential future directions. Some of the future directions identified include the use of directional antennas, wake-up radios, energy-harvesting and multi-hop MAC protocols.
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2.2. Access Management for Cellular M2M In cellular networks, devices also contend for access to the wireless channel. Because M2M networks consist of a massive number of devices, this necessitates the consideration of a highly effective contention resolution procedure i.e. an approach by which transmission collision can be resolved to ensure the effective utilisation of wireless radio resources. For example, there is a standard random access (RA) procedure that defines how devices attempt to access the channel and mechanisms for handling collisions in LTE. This procedure is necessary because devices contend while requesting for transmission or during reconnection after a failure. Measures that can be used for evaluation and performance comparisons of access management techniques for M2M in cellular networks include access delay, transmission success rate, energy efficiency and QoS guarantee of machine devices. These metrics can be defined as follows [5]:
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• Access delay refers to the length of time between the initiation and completion of random access procedure. • Success rate refers to the rate by which random access attempts are successful considering the maximum number retransmissions allowable.
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• Energy Efficiency refers to the total amount of energy which is spent during the access management process.
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• QoS guarantee refers to the ability of machine devices to meet peculiar service requirements such as delay.
With regards to the above mentioned measures, it is highly desired that devices are not delayed access beyond the application QoS constraint. The rate of transmission success should also be high. Another important factor to be considered is device mobility. For example, in applications such as 9
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Figure 4: Summary tables in literature and their references
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Figure 5: Summary tables in literature and their references
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vehicular M2M, the mobility of devices should be accommodated effectively without negatively impacting the overall QoS of the network. Solutions for medium access management were proposed by 3GPP for M2M communication in a cellular architecture. Solutions include access barring schemes, separation of RACH resources, dynamic allocation of RACH resources, back-off schemes, slotted access schemes, and pull-based schemes (where machine type communication devices (MTCDs) transmit data to eNB only when they are paged [59]) [5]. Suggesting that RACH contention is caused by high preamble transmission rate, [60] proposed a two-stage scheme based on controlling preamble transmission rates. The first stage is an auction approach for balancing and allocating traffic among periods, while the second stage is an RACH attempt estimation approach for controlling the preamble transmission rate decided by the first stage. For a variety of M2M applications, the proposed scheme is capable of handling access requests effectively. Some research directions are to [5, 61]:
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• investigate if a trade-off exists (and to what extent) between computation and communication costs for maintaining a clustered M2M network;
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• design energy-efficient access management protocols for event-driven applications;
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• ensure the availability of adequate control channel resources for massive M2M in cellular networks;
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• research the desired cluster size for massive hierarchical M2M in different settings; • address core network (CN) scaling or signalling because of congestion caused by concurrent signalling messages of machine devices;
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• develop hybrid pricing schemes to cater to the simultaneous access of machine and human traffic; • design LTE schedulers that can accommodate timing constraints and specific QoS requirements (latency, jitter, and guaranteed bit rate) for M2M communication within the Transmission Time Interval (TTI) of LTE; 12
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• design low-complexity schedulers for M2M in LTE/LTE-A;
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• design schedulers capable of catering to real and non-real time applications.
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Relevant Literature In ‘A survey of access management techniques in machine type communications’, [5] compared and classified several access management proposals for M2M communication based on metrics such as success rate, access delay, energy-efficiency, and QoS guarantees. This article has influenced other works including [43, 62, 63, 64, 65]. Reference [43] proposed a hybrid of adaptive slotted-ALOHA and TDMA to achieve resource utilisation in LTE/LTE-A under strict fairness constraints. Reference [62] presents an RA procedure for achieving resource efficiency and increased number of successful accesses. In [63], issues and proposed solutions for RAN and CN overload because of massive machine access are surveyed. Authors in [64] proposed a dynamic scheduler for LTE uplink that adjusts to network contention levels using traffic information. The scheduler supports M2M traffic and controls the impact of the Human-to-Human (H2H) traffic performance. Reference [65] presented a framework for analysing one-stage massive access. Using two approaches, the authors modelled and evaluated the channel occupancy rate and success probability. In the first approach, transmission from the devices arrive at the evolved Node B (eNB) with the same average received power. The second approach is Signal-to-interference-plus-noise (SINR)-based; where it was assumed that devices transmit with a constant power i.e. using channel inversion power control. The authors used analytical and Monte-Carlo simulation approaches to verify the results. The article ‘Is the random access channel of LTE and LTE-A suitable for M2M communications? A survey of alternatives’ [15], summarised the pros, cons, and future trends associated with alternative schemes proposed for improving LTE/LTE-A RACH operations. The authors expounded on the performance of the RACH in terms of energy efficiency to serve as a benchmark for future energy-efficient protocol designs. This article has also been referred to in [66, 67, 68, 69, 70, 71, 72, 73]. Authors in [66] studied the limit of M2M and H2H coexistence in LTE networks using thorough system level simulations. [69] focused on the physical layer (PHY) and MAC transmission technologies for IoT by comparing their performances. 13
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Recently, [70] considered RA in M2M communication with QoS, whereas [71] discussed machine type communication (MTC) with respect to its associated requirements, challenges, and solutions. [72] proposed an analytical framework for optimizing the random access performance of M2M communication. [73] presented a random access protocol based on DQ, with an estimation mechanism which can cater to over ten thousand simultaneous arrivals of traffic. In the article entitled ‘A survey of Traffic Issues in Machine-to-Machine communications over LTE’, [17] reviewed and classified proposed mechanisms for solving access traffic issues and traffic simulation models in the literature. Amongst others, [42, 74, 75, 76] have referred to this work. Reference [74] proposed a system for home automation suitable for large transducer deployment. The proposed system quickly recognises and configures transducers, thereby saving setup time and resources. For massive machine type devices (MTDs), [75] studied the design of uplink transmission for very short delay and high reliability requirements in tactile internet. Likewise, reference [42] considers a hybrid of collision avoidance and tree collision resolution in LTE for synchronised traffic in aircraft applications. Recently, [76] discussed issues relating to signalling and resource scheduling in LTE-based M2M/IoT networks characterised by small data transmissions. In this respect they reviewed literature on resource allocation in these networks. They further modelled the optimal behaviour of their previously proposed algorithm in [118]. According to the authors, a possible extension of this work is an evaluation of the energy-saved by the algorithm for M2M devices with small data transmissions. In ‘Classification of LTE Uplink Scheduling Techniques: An M2M Perspective’ [61], the authors surveyed uplink scheduling techniques for M2M over LTE/LTE-A and presented a classification of LTE scheduling techniques based on multi-hop and scalability, QoS parameters, and power savings. A main contribution is its exposition of different schedulers for LTE-A and the complexity of various scheduling algorithms. Amongst others, [61] has been referred to in [78, 79]. Reference [78] introduced a scheduling metric called ‘Statistical Priority’, which demonstrates the peculiarity of some packets sent by MTCDs. Data with non-redundant information is scheduled with a higher priority to properly manage radio resources. This approach results in a lower number of deadline misses for critical data. The authors in [79] modelled the energy consumed, and investigated the impact of scheduling and power control on the battery lifetime of machine devices in cellular-based 14
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M2M networks.
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2.3. Access Management for Capillary M2M A capillary network is a local network which deploys short-range radioaccess technologies to provide connectivity to groups of devices [80]. Capillary M2M network consists of machine devices supporting technologies such as Zigbee, Bluetooth, WiFi, ultra-wide band (UWB) and Smart Utility Networks (SUNs). The network uses Industrial Scientific Medical (ISM) band which eradicates the problem of interference with cellular users. Capillary M2M can also ‘aggregate and shape’ M2M traffic transported to a wired, wireless or cellular network such as WiMAX and LTE [81]. Capillary M2M networks have advantages over cellular M2M networks, considering peculiar perspectives. For instance, devices can connect to free unlicensed band radio access technology (RAT) in capillary networks. Although, cellular M2M networks enjoy highly reliable communication and wider coverage, capillary M2M can be effectively deployed in areas with poor cellular coverage such as basements and indoor environments. ZigBee can be effectively deployed in smart homes as it can cater to low power and low-rate applications, whereas Bluetooth Low Energy (BLE) can be effectively used in home automation because of its ultra-low power consumption [18]. Capillary M2M networks are also cost-effective for handling a large number of M2M devices as compared to cellular M2M [82]. Generally, the unique characteristics and general requirements of M2M must be considered when choosing the appropriate technology for access management and during protocol design. Wireless Fidelity (Wi-Fi) for instance has a current service range of 100 m in Wireless Local Area Networks (WLANs), which is quite short to cater to densely deployed MTCDs in large outdoor environments. Therefore, IEEE 802.11ah (Wi-Fi HaLoW) catering to diverse QoS requirements can be integrated into Wi-Fi products, since it can be flexibly configured for different applications [18]. Currently, IEEE 802.11 is one of the wireless technologies being modified for use in IoT because of its wide-range deployment and support for IP connectivity. Therefore, it is promising for energy-efficient and low-cost wide-scale M2M deployment as affirmed in [83]. Some of the issues associated with specific access management in capillary M2M technologies are as follows [18, 81]: • Wi-Fi: Wi-Fi may not fully satisfy the diverse QoS requirements for MTC, it may have to be modified to suit different use-cases. 15
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• IEEE 802.11 standard: Customised solutions for IEEE 802.11 may have to be devised to cater to diverse MTCD applications.
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• ZigBee: Mesh ZigBee networks are characterised by low utilisation as they have no beacons. Tree-based topologies also have limitations which manifest in a lower transmission efficiency and tight synchronisation. Asides the aforementioned, future extensions to these networks should also consider effects of interference, fading and channel quality.
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• Bluetooth: This has energy management issues as well as terminal grouping and data aggregation when M2M terminals are to connect in a piconet (network devices connecting via Bluetooth) [81] as investigated in [84, 85].
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• Coexisting RATs: For the coexistence of technologies such as ZigBee, SUNs, and Wi-Fi, sharing the unlicensed band radio resources is critical and requires proper management. RATs must coexist in a manner that ensures minimum interference [18]. In addressing interference which could occur due to the coexistence of IEEE 802.15.4 and WiFi, inactive periods in the WiFi channels could be exploited [81].
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In addition to the above mentioned issues, it is important to reiterate that these capillary technologies should be able to support heavy M2M traffic in areas such as residential and business areas. Also, MAC protocols which can function with terminals with multiple radio interfaces (such as IEEE 802.11 and IEEE 802.15.4) should also be developed, so that devices can then use whichever technology provides the best connectivity. TV white space could also be deployed to extend the transmission range, especially in less populated areas. Finally, data aggregation should also be supported in gateways for capillary network [81].
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Relevant Literature In the article ‘Radio Resource Management in Machine-to-Machine Communications - A Survey’ by Xia et al.[18], the authors presented a comprehensive survey of research activities related to access control, power management, and radio resource allocation for M2M communication. A detailed discussion on unlicensed band RATs for capillary M2M communication was provided. A unique contribution of this paper is its categorisation of themes for radio resource management in LTE/LTE-A. The authors also identified 16
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open directions with respect to NB-IoT, Sparse Code Multiple Access 1 and software defined network (SDN)-based M2M, amongst others. In the paper entitled ‘Physical layer architectures for machine type communication networks - a survey’ [82] discussed the PHY features of capillary technologies such as Wi-Fi, Bluetooth, ZigBee, and SUN. They proposed an air-link design based on complementary-coded code division multiple access (CC-CDMA). This is suitable for the gateway to small-cell access point interfaces and serves as a ‘complement’ to current standards and technologies. With respect to this, the authors also reviewed CC-CDMA and M2M challenges for future wireless communication. Wang et al.[88] surveyed LPWA, IEEE 802.11ah, and cellular network infrastructure solutions for M2M in the paper entitled ‘A survey of enabling technologies of low power and long-range machine-to-machine communications’. Research gaps and future directions were identified to improve the performance of these low power and long-range technologies. Further related works to [88] include [81, 82, 89, 90]. The authors in [81] discussed the current challenges of capillary M2M communication technologies such as the development of charging policies for service providers and addressing security issues. [89] surveyed technical aspects and use-cases of future IoT-based healthcare applications. In light of this, the authors examined current and emerging technologies, standards, and requirements for such applications with special attention on short and long-range communications. They concluded that an amalgam of existing technologies would be required to cater for future healthcare application. The authors in [90] performed an experimental study to analyse the signalling overhead for M2M services suitable for smart metering and vehicular applications. They proposed techniques for signal reduction by considering signal aggregation to tackle issues associated with a surge in signal overloads.
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3. Home M2M M2M communication has a variety of applications in homes. Examples include surveillance, multimedia streaming and sharing, and energy management systems for smart grid and healthcare. When considering radio service 1 Sparse Code Multiple Access [86] can be regarded as a code division multiple access scheme characterized by sparse codebooks [87]
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Figure 6: Key illustrations in the literature and their references
range and applications, home networks involve body, personal, and local sub-area networks [21].
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3.1. Architecture According to 3GPP, network terminals interconnect in two ways, either cellular or capillary M2M communication. In the first case, M2M terminals directly connect to the cellular (3G or 4G) network. In capillary networks, devices connect using wireless links and data is relayed to the cellular network using a gateway [21, 91]. As shown in Fig.7, the cellular M2M architecture is basically composed of three major components such as machine devices, gateway, and eNodeB. The interaction of these components within the network results in four different forms of communication: devices can communicate mutually, they can connect to the gateway or the eNodeB, and the gateway can also communicate with the eNodeB. In this regard, a proper architectural design is required to guarantee the necessary QoS requirements.
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Some trade-offs must be considered in the design of any network architecture. For instance, in a capillary home M2M network, the coverage per device may be very low when compared with cellular M2M. Other issues associated with home M2M network design include radio interference in home areas, unreliable wireless channels because of fluctuation and noise, nature of devices (e.g. heterogeneity and resource constraints), and self-organisation and QoS support [21]. In addition, an architecture with gateways requiring data aggregation should ensure a proper selection of the relay node. In architectures with cognitive gateways, the gateway should be capable of autonomously interacting with the surrounding environment and adaptively changing the transmitter settings when required.
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Relevant Literature Zhang et al. [21] presented a survey entitled ‘Home M2M Networks: Architectures, standards and QoS improvement’ identifying challenges associated with M2M networks. A QoS and resilience -aware cross-layer joint admission and rate control for multimedia sharing was further proposed. An investigation into this approach with a joint design demonstrated that in resource constrained home M2M networks, the proposed method can allocate radio bandwidth intelligently based on the QoS. In addition, the QoS rate control, a unique feature of [21], is its M2M architecture that supports several technologies. This work has been referred to in [92, 93, 94, 95, 96]. Reference [92] classified M2M in terms of context, task, and objective with a review of recent issues and solutions. [93] addressed radio resource allocation for energy-efficiency in cellular M2M. [94] discussed M2M security challenges in 3GPP and potential solutions. [95] focused on latency, energy savings, and reliability for uplink and downlink M2M with performance analysis. Authors in [96] considered reducing uplink requests for M2M using the grouping and compression approach in the gateways.
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3.2. Technologies Home M2M involves the co-existence of several technologies. The technologies can include Bluetooth Low Energy, short-range radio technologies such as ZigBee, and broadband such as UWB. These technologies come with their merits and demerits. For instance, Bluetooth performs well in terms of energy but has latency issues in large deployments. On the contrary, ZigBee can guarantee low power consumption and longer lifetime, thus, it is used in capillary M2M networks. Similarly, broadband technologies such as 19
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UWB and HomeRF provide high throughput at the price of increased energy consumption [22]. Emerging radio technologies applicable in home networks include IEEE 802.15.6, which is used in medical applications for helping the disabled, 60GHz transmission, and visible light communications [22].
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Relevant Literature The article ‘A survey of recent developments in home M2M networks’ [22] discussed M2M technologies and applications such as entertainment and health and energy management. An examination of home M2M network architectures, performance trade-offs associated with designs, and QoS provisioning methodologies were also conducted. This work has been referred to in [97, 98, 99]. [97] surveyed device-to-device communication (D2D) in cellular networks, [98] reviewed networks for home automation, and [99] considered challenges associated with cognitive radio for future mobile networks. Chen and Lien [4] summarised the technologies for achieving highly efficient machine swarm communication in the paper entitled ‘Machine-tomachine communications: Technologies and challenges’. This aims to facilitate a realisation of wireless M2M infrastructure on the cloud with a massive number of machine devices. [4] also highlighted related enabling technologies for wireless M2M communication. This work has been referred to in [100], which studied the interaction between fog computing and D2D communication for low-latency M2M communication to be configured on an LTE-A platform. Reference [101] studied the definition and classification of white spaces for cognitive radio. [102] considered the interference challenge associated with licensed-assisted access in cellular networks. Authors in [103] investigated statistical networking to attain reliability and QoS guarantees. Reference [104] surveyed cognitive technologies and models for improving the efficiency of M2M communication. 4. Mobile M2M
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Mobile smartphones in cellular networks, vehicle-to-vehicle applications [5], and logistics and e-health [23] constitute interesting applications enabled by M2M communication. For instance, smartphones can play a major role by serving as mobile gateways for energy constrained machine devices in applications such as heart monitoring systems, where the smartphones can be used to receive data [11]. As there has been considerable research on
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wireless body area networks, more studies on the use of smartphones in health applications for M2M are required.
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4.1. Mobile M2M in cellular infrastructure Optimising current cellular network solutions for mobile M2M is a matter of necessity [9]. Mobile M2M applications in the context of cellular networks such as LTE and LTE-A can benefit immensely from the cellular architecture in terms of extensive coverage, high reliability, and reduced cost. However, performance degradation should be avoided by ensuring proper spectrum allocation and utilisation. In a bid to achieve spectral efficiency in the network, issues concerning interference must be properly addressed. In addition, scheduling schemes proposed to achieve proper channel utilisation should duly consider traffic differentiation. Using the resource partitioning approach, RA overload2 control should be made to work in tandem with proper back-off procedures and eNodeB selection. Development of energy efficient transmission schemes using smartphones to function as mobile gateways can be achieved through methods such as transmission scheduling, header compression, and data aggregation [11]. However, future research can leverage heterogeneous networks to address this issue. Other relevant issues include [11, 24]:
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• Evaluation of resource usage efficiency in mobile M2M communication. For instance, how do diverse traffic patterns from machine devices affect mobile M2M communication?
2 RA overload occurs as a result of massive random access in dense LTE-A networks [66, 19]
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Relevant Literature The paper entitled ‘Towards efficient mobile M2M communications: Survey and open challenges’ [11] provided insights into reference architectures for M2M with a focus on European Telecommunications Standards Institute (ETSI) network architecture. A major contribution of this work is its exploration of the use of smartphones as gateways for M2M communication. Related research includes [20, 105, 106, 107]. [20] surveyed technologies and networking techniques for M2M communication with their associated limitations. Similarly, they discussed short-range capillary networks and application development protocols. [105] evaluated latency performance in IoT using mobile gateways. [106] studied a ‘D2D-based IoT data collection’ scheme. In this approach, an IoT device aggregates data collected from smart objects (using D2D links) towards the eNodeB by using a Modulation and Coding Scheme (MCS). Motivated by the use of satellites to cater to a fraction of the M2M/IoT data, [107] proposed a congestion control mechanism in the random-access satellite channel which can be configured at the application layer. In the review paper entitled ‘Mobile M2M communication architectures, upcoming challenges, applications, and future directions’ [24], the authors discussed reference models, architectures, service requirements, standardisation efforts, applications, challenges and future directions related to mobile M2M. Some of the notable papers that have referred to this work include [108], which surveyed radio resource management for energy-efficiency in cellular networks, and [109], which presented a survey on networks and technologies for smart cities. Recently, [110] discussed current advances, architectures, and research challenges associated with M2M technologies.
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4.2. Vehicular M2M Autonomous vehicular communication is one of the key applications of M2M communication. Its applications are extensive and its implications are beyond current expectancies. Particularly, this technology can reduce transportation costs. For instance, driverless cabs are expected to make transportation more accessible to low-income households [111] who may not afford to own cars. Other applications include safety and collision avoidance, management of traffic and infrastructure, vehicle telematics, and in-car entertainment and internet services. Owing to the unique mobility patterns associated with vehicles as compared to cellular devices, vehicular networks are characterised by an architecture consisting of five major parts that include intra-car 22
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networks, vehicle-to-vehicle (V2V) networks, vehicle-to-infrastructure (V2I) networks, backhaul, and servers [23]. Sensors and car-instruments (e.g. airbag system) can collect data while Media Oriented Systems Transport (MOST) ring facilitates intra-car communication. An On-Board Unit (OBU) and the bus master on the MOST ring can aggregate data. Similarly, Wireless Access to Vehicular Environment (WAVE) can be deployed for intra-vehicle and extra-vehicle communication. Through the MOST ring, media can connect to infrastructures through wireless technologies with high bandwidth such as Wi-Fi, Worldwide Interoperability for Microwave Access (WiMAX), and cellular networks for video, audio, or internet services. Road side units and access points for high-bandwidth technologies can function as gateways to Intelligent Transport System (ITS) and internet as backhaul services. Using the internet and ITS, vehicles can communicate with back-end servers [23]. In the pursuit of effective autonomous vehicular communication, it is important to ensure that involved entities in communication can be visualized. Devices should also be easy to control and the process of sending reports should be automated. A few other necessities include [23, 111]:
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• vehicular network autonomy that would help to achieve security, centralized management systems, and dynamic connectivity;
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• mechanisms that would address the challenges of V2V and V2I connectivity;
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• cross-platform networking for inter-vehicle and intra-vehicle communication;
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• adapting to the dynamic evolution and diversity of consumer electronic devices;
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• mechanisms that would discreetly accommodate the unpredictable movement of nodes that could hinder proper inter-vehicle communication; • preserving privacy of vehicular users such as traffic reporting; • mechanisms for efficient vehicle routing so that autonomous vehicles could easily determine appropriate routes in road networks; • addressing operational setbacks associated with the functionality of electric vehicles such as battery durability, size and lifetime. 23
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Relevant Literature In the article entitled ‘Machine-to-Machine Communication in Vehicular networks’, Booysen et al.[23] described the generic M2M architecture and the communication standards associated with vehicular networks such as Controller Area Network (CAN), MOST, WAVE, Wi-Fi, WiMAX, and cellular standards. This work has been referred to in [112, 113, 114, 115]. Reference [112] gave insights into vehicle electrification and intelligent transport systems for future smart grid networks considering the entities and components involved. They discussed electrified transportation with respect to societal adaptation and communication perspectives. [113] presented a survey on cooperative platoon-based driving with physical dynamics in Vehicular adhoc Networks (VANETs). [114] surveyed current approaches targeted at the deployment of smartphones to enhance ITS including the opportunities and challenges associated with smartphone-assisted driving. Reference [115] considered Internet of Vehicles (IoV) and proposed a framework for layered architecture to address relevant problems. In the article entitled ‘Autonomous vehicles: challenges, opportunities, and future implications for transportation policies’ [111], the authors discussed an array of issues including ethical challenges and opportunities associated with autonomous vehicles with respect to transport policies. They presented a navigation model for effective ‘traffic circulations’ in autonomous vehicular communication. The relationship and differences between machine-to-machine communication, wireless sensor networks, cyber physical systems, and Internet of things were considered in ‘Machine-to-Machine Communications: Architectures, Standards and Applications’ [13]. The potential of a cyber-transport system to enhance road safety was shown in the form of a novel system that brings together the concept of an unmanned vehicle using sensor navigation and an intelligent road to avoid intersection collision. Further research challenges were also identified. Works that have referred to this article include [116, 117, 118, 119, 120]. Reference [116] proposed an autonomous, secure, and economic M2M system for e-health. The proposed system also accommodates dynamic allocation of medical doctors. Reference [117] presented a 4-layered IoT architecture with an intelligent system based on Radio Frequency Identification (RFID) for M2M communication. Authors in reference [118] considered the priority scheduling approach deployable in applications requiring instantaneous
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5. Standards and Service Platforms
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response such as healthcare. Reference [119] presented event-driven architectures for M2M communication. [120] considered a framework for smart home applications, incorporating several previously proposed frameworks and architectures.
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One of the key constituents for the rapid development of M2M markets is standardisation activities [7]. This is quite challenging because of the wide range of M2M applications. Consequently, the scope of standardisation efforts becomes wider than other traditional networks [24]. Consequently, several standards development organisations are making efforts to facilitate M2M communication. Among these are 3GPP [121], ETSI [122], Internet Engineering Task Force (IETF) [123], oneM2M [124] and NB-IOT [125]. 3GPP provides a stable environment for members to produce reports and specifications that are used to define its technologies. Amongst others, the 3GPP technologies include radio access, core transport network, and service capabilities. 3GPP consists of seven member telecommunication standards development organisations [121]. ETSI is concerned with developing standards that are globally applicable for information communication technologies. These include fixed, mobile, broadcast, and radio and Internet technologies. It is a large body consisting of eight hundred member organisations from sixty-six countries and five continents [122]. The IETF is an international community involving several stakeholders such as network designers, vendors, operators, and researchers working towards the smooth operation of the Internet and the evolution of its architecture [123]. oneM2M is a global standard initiative targeted at M2M and IoT. To address the need for a uniform service layer that can be embedded in various hardware and software, oneM2M develops the required technical specifications. Furthermore, oneM2M is also concerned with the reliable connectivity of several devices with M2M servers all over the world [124]. NB-IoT is a new narrowband radio technology standardised by 3GPP and completed in 2016. It is aimed at addressing the requirements of IoT such as coverage, support for massive devices, low power consumption, low cost, and optimised network architecture [125].
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5.1. Standards’ Requirements Because multiple stakeholders are involved in M2M, it is essential that M2M systems should be based on open standards as their lifetime would be extended for over many years. In addition, standards must be rapidly developed for interoperability and global market and economies of scale support as needed by the industry. Standards should also support multiple classes of delay using an enforcement delay mechanism for the development of M2M/IoT applications. This can be done by leveraging the pros of standards such as Differentiated Services (DiffServ) and Integrated services (IntServ) for QoS requirements. For applications such as smart home, semantics and relevant data are required in the abstraction of such M2M use-cases. The use of information semantics would also cater to the need of providing common enablers to M2M applications for discovery, interpretation, and utilisation of data from different sources [25]. Several open issues associated with standards include [25] and [6, 10, 27, 32]: • the need for working on adequate device management (on a large scale) and remote software management;
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Relevant Literature In the paper entitled ‘M2M Communications for E-Health and Smart Grid: An Industry and Standard Perspective’, Fan et al.[10] discussed M2M standardisation activities analysing their enabling technologies and industrial applications. Smart grid and e-health were discussed as typical examples of
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M2M applications with a summary of ongoing industrial and standardisation efforts. The discussion entailed academic perspectives published in the literature and how they are augmented. Reference [10] has been referred to in [126, 127, 128]. [126] discussed meta-architectures for harmonising standardisation technologies, including architecture and protocol interoperation for smart grids. [127] surveyed 5G mobile networks while [128] surveyed challenges for M2M in smart grids. In ‘A survey of standards for Machine-to-Machine and Internet of Things’, Gazis [25] reviewed major challenges of future standardisation in IoT. The features of several standards and architectures were summarised and classified under different headings such as progress/release state, internet protocol stack layer, and deployment perspective/coordination model. Classification was based on supported domains, architectural styles, and contributed definitive elements. Amongst others, this work has been referred to in [129, 130, 131]. [129] surveyed real-time analytics and other proposed network methodologies for IoT. Reference [130] estimated the quality of transmission and spatial frequency reuse and optimised massive IoT systems. [131] considered security standardisation for IoT. The article ‘Machine-to-Machine (M2M) communications: A survey’ [7] presented a generic system model for the device, network, and application domains of M2M. Several system models and architectures proposed by different standards developing organisations such as 3GPP, ETSI, and oneM2M were also discussed. A characterisation of M2M data traffic was performed by various standardisation bodies and their specific tasks. This work has been referred to in papers such as [132, 133, 134, 135]. Reference [132] studied the clustering algorithm for MTC over LTE for data processing by considering mobility. Authors in [133] studied localisation problems among ‘blind’ machine devices in ‘noisy’ environments. [134] considered the deployment of M2M communication to enhance fault-detection accuracy in industrial applications. Reference [135] considered an analytical approach for medium access control to investigate the performance of M2M and D2D communication with unlicensed resources. 5.2. Service Platforms To ensure interoperability, ease of discovery, and proper management, M2M systems should be managed with an appropriate level of abstraction. In this manner, devices can be organised to collaborate and share complex 27
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information. The platforms on which the devices are managed can be referred to as M2M service platforms [136]. As discussed by Kim et al. [26], M2M platform models can be classified based on commercialisation and research. The first class of M2M platform models include a customer-to-customer and business-to-customer model that would be beneficial to individual users with a limited number of different devices. Devices can periodically send data to subscribers based on events. Objects can also be collected from sensors, which can be retrieved from the access gateway. The second class of M2M platform models are research-based, which accommodates both authorised personal user devices and public devices. Smart object resources are shared through virtualisation and can be searched and discovered. These platforms are not devoid of requirements vital for successful application. In the industrial domain, major players associated with service platforms have to establish an ‘ecosystem’ that would reduce the cost of development and the time to market M2M devices. The service platforms must also be supported by enabling technologies and standardisations. This would help bring down development cost, reduce the time to market M2M services, and achieve service-convergence among industries through data sharing. Other requirements are given below [26]:
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• Internet-connected objects must be registered to platforms where they can be authenticated, searched, and modified; • Platforms should have the ability to autonomously control and instruct devices and actuators in reaction to collected data;
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• Apart from managing individual devices, functionality should also be supported by the platform;
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• Smart devices should be capable of accessing services using an application or the web. The app store can be managed by the platforms;
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• Platforms offering cloud services should be able to store data from sensors and objects; • Interoperation and mutual connection of M2M devices should also be supported; • Platforms should have the capability of being accessed via the internet at any time and from any location; 28
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• Platforms should have the ability to provide peer-to-peer (P2P) communication support;
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• It is also necessary to develop an M2M platform to realise the future conception of M2M services.
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A typical service platform architecture such as M2M Service Platform (M2SP) [26] can include an M2M area network, access network, and a CN. The M2M area network consists of heterogeneous networks with a sink that connects the network through access networks. The CN accommodates various traffic types from several objects and provides reliability and QoS guarantees for such traffic. Users and objects connected to the CN are managed and M2SP provides services. A typical scenario that illustrates the manner in which different components and stakeholders interact is a vending machine. In this case, a user can find the location of a vending machine with a specific product. The service provider manages the stock of vending machines and provides product details and advertisements. Some issues and future considerations for service platforms are given below [26, 27]: • Processing management information in bulk can reduce network performance degradation because of dead nodes.
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• Enabling virtualisation of M2M communication. • Developing solutions to realise autonomic service networks.
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• Considering P2P communication to reduce delay and efficiently handle unnecessary traffic. However, for massive M2M, a signalling process for authorization between devices and resource allocation is required.
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Relevant Literature In the article [26] entitled ‘M2M Service platforms; survey, issues, enabling technologies’, a service platform architecture with a sample service scenario was proposed. Several application use-cases were provided to demonstrate the way components of this platform interacted. The authors further discussed standardisation activities in international standards organisations (ISO) and provided future research directions. Some works that have referred to this paper include [137, 138, 139, 140]. [137] thoroughly studied 5G wireless evolution, [138] considered pricing models in 29
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Wireless Sensor Networks (WSN), M2M and IoT while [139] reviewed RA procedures and probable solutions for satellite networks. [140] deployed use cases consisting of several platforms to evaluate inter-networking interfaces using oneM2M. The authors of ‘Machine-type communications: Current status and future perspectives of 5G systems’ [28] ‘mapped’ MTC requirements and their likely solutions. They provided a picture of current cellular technologies progressing towards MTC in 5G mobile systems. Similarly, the service functions, requirements, applications, and corresponding issues were discussed. This paper has been referred to in [141, 142, 143, 144]. Authors in [141] surveyed security threats and solutions in MTC and further presented an authentication scheme for scalable LTE heterogeneous networks. [142] presented a dynamic resource allocation mechanism using learning automaton (LA) to assign resources to devices based on their priorities. [143] surveyed notable advancements in technology for 5G wireless communication including issues and possible solutions. Authors in [144] surveyed unmanned aerial vehicles (UAVs) using MTC for IoT.
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The LTE technology is growing rapidly [145] and is being enhanced to support new applications and technologies in recent years. LTE-A is an enhanced version of the LTE cellular network [146]. The LTE/LTE-A network is of particular interest as it can cope with the increased usage of mobile data and multimedia applications [147]. Next, we briefly introduce the LTEA architecture which supports M2M communication and highlight some of its challenges.
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6.1. Network Architecture As shown in Fig. 7, an LTE network consists of the Evolved Packet Core (EPC) and the Evolved Universal Terrestrial Radio Access Network (E-UTRAN). The E-UTRAN comprises of eNBs that are connected to each other by the X2 interface. The S1 interface connects each eNB to the EPC. The serving gateway (S-GW) is terminated by the S1 interface on the user plane, while on the signalling plane, the S1 interface terminates the Mobility Management Entity (MME). To enable M2M communication, machine devices can connect to the eNB directly or through a gateway. Services are
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Figure 7: A basic LTE/LTE-A architecture with M2M communication
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provided by MTC servers that can be accessed by the users in the application domain [92]. Machine devices can also connect to each other in a P2P fashion. Cellular M2M networks play a key role in wireless infrastructure. A flexible network architecture is required, keeping in view the present and future technologies. Because it is necessary to centrally locate data obtained from M2M devices, a cloud-based solution will be highly propitious and would help achieve cost efficiency, scalability, continuous availability, and accessibility [4, 7]. 3GPP has made provisions to accommodate MTC at the physical layer of the LTE architecture [148]. 3GPP LTE and LTE-A have several advantages over other access technologies because they have a flexible radio resource management scheme. However, they were not envisioned for applications characterised by small amounts of data like M2M applications. They are used for wideband applications. The consequence of this is an inefficient utilisation of technology [29]. As such, there is a need for a standard end-to-end architecture to integrate 31
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network solutions from different MTC stakeholders. This would help to give reliable interconnectivity between devices all over the globe. Constructing and managing connections among several MTC devices distributed over a vast area has several challenges. For instance, in the case of an air interface (i.e. the radio-frequency-based connection/communication medium between the mobile base station and user equipment [149, 150]), there are challenges associated with the use of current H2H mechanisms for M2M communication. The challenges include PHY transmission issues, RA procedure issues, energy and complexity challenges, and radio resource allocation for critical QoS provision [6]. Another major problem in MTC cellular networks is congestion due to simultaneous signalling messages from machine devices, possibly resulting in peak load situations [151]. This negatively affects mobile network operation and performance of critical nodes with limited resources. To address this problem, a bulk signalling handling approach can be used [9]. Using this scheme, similar signalling messages from MTC are handled in bulk. This approach can be used as a complementary or alternative method of controlling network congestion and overload in M2M. Extending network coding and random data combination is required for reliability and error control in heterogeneous M2M communication in 3GPP LTE/LTE-A. The network coding provides an effective means to achieve efficient and reliable transfer of data. It also requires very little coordination among nodes. Distributed processing paradigms can also be considered for decoding in dense M2M networks. In addition, ensuring efficient and timely analysis of data gathered by M2M devices can be achieved using various machine learning techniques. However, it should be noted that this requirement depends on the application. Other challenges associated with M2M network architecture include [6, 9, 29]: • ensuring connectivity, compatibility, and interoperability within M2M communication network;
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and M2M devices through more Evolved Universal Terrestrial Radio Access (E-UTRA); • characterising M2M traffic to handle several QoS requirements;
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• developing more reliable transmission mechanisms;
• considering unsophisticated, fixed, and conservative techniques for the design of link adaptation;
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• determining whether additional resources shall be allocated for the Physical Downlink Control Channel (PDCCH) and whether the PDCCH shall be separated for MTC devices and UEs.
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Relevant Literature The article entitled ‘Machine Type Communications in 3GPP Networks: Potential, Challenges, and Solutions’ [9] focused on 3GPP Release 10. The authors proposed a bulk signalling handling approach for congestion control and network overload avoidance. [9] has been referenced in [152, 153, 154, 155].Reference [152] examined mobile telecommunication trends, issues, and the possibility of bringing the cloud service to mobile users. [153] presented enhancements for M2M and IoT in 3GPP concerning architecture, management, monitoring, power, and latency. [154] studied the significance of multihop-based D2D communication in extending M2M network coverage and range. Authors in [155] focused on physical control channel issues for LTE-based M2M communication with a proposed solution for handling physical limitations associated with M2M devices. In the survey entitled ‘M2M Communications in 3GPP LTE/LTE-A Networks: Architectures, service requirements, challenges and applications’,[29] presented enhancements concerning LTE/LTE-A architecture in M2M networks and examined challenges of M2M over 3GPP, LTE/LTE-A. This work has been referenced in a number of research papers including [156, 157, 158]. The authors in [156] focused on using a dynamic grouping approach controlled by the gateway to reduce signalling overhead in MTC over LTE. Authors in [157] proposed an approach to determine the required number of preambles to achieve maximum throughput for an unknown number of devices and access probability. Recently, [158] presented a detailed survey on cognitive radio for machine-to-machine communications. In this respect the
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authors discussed challenges and benefits associated with the amalgamation of these technologies. Lien et. al [6] presented an overview of M2M features and network architectures in 3GPP and LTE-A in the survey entitled ‘Towards Ubiquitous Massive Accesses in 3GPP Machine-to-Machine Communications’. The challenges related to an air interface of LTE-A were examined. An effective grouping-based radio resource management was proposed to facilitate M2M applications with strict timing constraints for QoS guarantees. This survey has been referenced in articles such as [159, 151, 160, 161, 162, 163, 164, 165]. [159] studied RACH overload and key challenges in LTE-A. [151] addressed the congestion issue in MTC using congestion-aware admission control. [162] proposed a dynamic overload control algorithm to resolve congestion at the RAN because of massive M2M device requests. Reference [163] put forward a group model based on MTD traffic to achieve efficient resource management for MTC. [164] proposed an RACH for 5G MTDs that transmit small packets within the RA burst. This allows machine device detection, decoding, channel estimation, and security authentication. Recently, [165] analysed a new Millimeter wave-non-orthogonal multiple access transmission mechanism for achieving QoS guarantees in cellular M2M. The authors also proposed an BSto-MTD distance-based device pairing schemes to cut overhead and latency in cellular M2M networks.
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6.2. Ultra-dense Networks One of the main technologies that would enable future wireless communication is Ultra-Dense Networks (UDNs) [30]. UDNs have several unique features that set them apart from traditional cellular networks. First, the number of communication links and (or) access nodes are densified for each unit of area. In other words, there are many small cells in the vicinity of each user. This would mean that several of these small cells would also be inactive. From the above description, an increase in the density of small cells would mean a high level of interference. In addition, very innovative approaches for handling frequency reuse would be required. Another feature of UDNs is that line-of-sight (LOS) communication would be higher. However, achieving low-delay and high-speed backhaul would pose challenges to network designers [166]. Because M2M communication will become a vital component of future 5G wireless networks consisting of UDNs, there is a need for comprehensive studies on M2M in UDNs. Application scenarios of M2M in UDNs include 34
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apartments, industries, enterprises, and hotspots. Although, cellular networks inherently include UDNs, implementing M2M communication poses peculiar challenges at different layers of the protocol stack [30]. In relation to the PHY layer, supporting multiple non-cellular technologies is a challenge especially in Small cell Base Station (SBS)-based or distributed antenna system (DAS)-based UDNs. In other words, cellular and non-cellular interfaces should be accommodated by either machine-type gateways or Small cell Base Station/Radio Remote Head (SBS/RRU). However, a different design of SBS/RRU is required for other configurations. An advantage of this approach is that the expense of deploying machine-type gateways will not be an issue of concern [30]. In relation to the MAC layer, four major challenges must be considered for implementing M2M communication in UDNs: • Concurrent access of machine devices;
• Resource allocation efficiency because H2H and M2M would co-exist within the network.
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• Interference mitigation schemes for machine devices working in the same band;
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• Appropriate selection of RATs for machine devices.
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In the network layer, finding an appropriate routing mechanism is the most paramount concern. This can be achieved in several ways using machine-type gateways or UEs as relay nodes between machine devices and the CN. Similarly, the BS could also be used for data relay. The application layer requires improvements to ensure that resources are not wasted because of M2M communication. In this regard, the waiting time of machine-type devices can be made dependent on latency requirements. It is necessary to design protocols that efficiently accommodate the unique characteristics of M2M traffic [30]. In the physical and medium access layers, some modifications or enhancements might be necessary. The main research questions related to the implementation of M2M communication in UDNs are as follows [30]: • Supporting non-cellular M2M networks in UDNs; • Improving transmission efficiency for M2M in UDNs; • Minimising the number of required active gateways for M2M in UDNs; 35
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• Designing priority-based resource allocation mechanisms for machinetype and H2H communication; • Efficient separation of M2M and H2H traffic at base stations;
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• Efficient coordination among BS by grouping or clustering the BSs; • Defining new service categories for several M2M applications.
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Another promising direction in UDNs is highly efficient device positioning for location-aware applications. Specifically, robots, drones, and vehicles can be accurately tracked for use in factories, intelligent transport systems, and autonomous cars [167]. This is propitious for several M2M applications.
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Relevant Literature In the article entitled ‘Machine-to-Machine Communication in UltraDense Networks: A Survey’ Chen et al., [30] married M2M and UDNs that have usually been separately considered in the literature. To support M2M in UDNs, they explored several service categories for small data transmission. Some papers that have referred to this work include [168], which achieved optimal throughput and scalability in ultra-dense multi-cell RA scenarios using a decentralised approach to transmission suited for machine communications. [169] proposed a security-aware mobile relay selection algorithm for M2M devices using multiple UEs. The relay perform aggregates and transmits data to the BS.
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7. Energy Efficiency, Reliability and Security
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The growth of M2M communication rests on understanding and managing the challenges of M2M. Among these challenges are energy-efficiency, reliability, and security (GRS) [2]. This section discusses issues related to energy-efficiency and reliable and secure M2M communication. Specifically, subsection 7.1 and 7.2 highlight issues related to energy-efficiency and reliability, respectively. In subsection 7.3, we present an overview of security issues with respect to M2M communication. We excluded technical details because of space considerations.
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7.1. Energy Efficiency In the context of wireless networks and mobile devices, one of the objectives of achieving energy-efficiency is to increase the battery life of devices. Specifically, energy-efficient communication is motivated by reducing the impact of C02 emission and to counter-balance the increasing cost of energy sustained by network operators [170]. Energy efficiency is crucial to the success of M2M communication. Many of the M2M applications require devices to operate for a long period of time with constraints in terms of computation power and battery life. Whenever M2M performs monitoring functions, data redundancy and energy loss can occur, which negatively affect the network lifetime. Therefore, for M2M networks to perform effectively, energyefficiency must be the focus of consideration. This is also important for environmental protection [31]. Energy efficiency can be realised in several domains using radio optimisation, data reduction, sleep/wakeup schemes, battery repletion, and architectural and proprietary energy saving methods. The reduction of energy loss can be achieved through several approaches. For instance, energy efficiency of monitoring devices can be improved by regulating their active modes [31]. Other insights into energy-efficiency actualisation and power optimisation include [7, 31, 171]:
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• Proposing self-adaptive and energy-efficient routing protocols for M2M; • Including precise location information in protocols because of their effect on planarisation techniques;
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• Investigating the required number of hops for efficient communication with the cellular backbone;
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• Harvesting energy from natural sources (such as temperature, light, and mechanical sources);
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Relevant Literature In the article entitled ‘Energy efficient techniques for M2M communication: A survey’ [31], the authors classified energy-efficient techniques with respect to the optimisation of radio, reduction of data, sleep/wakeup schemes, battery repletion, architectural and proprietary techniques for energy saving in M2M. They compared and analysed energy efficient algorithms. A key feature of this paper is the classification of energy-efficient techniques based on the OSI model using equations and algorithms. Although, several papers were properly grouped into sections, they were not criticised. Apart from several papers, this study has been referred to in [172] and [173]. Reference [172] surveyed current research issues in M2M, specifically in smart grid scenarios. The authors also presented M2M standards advancements and the potential of cognitive radio for big data communication. [173] investigated clustering approaches for enhancing the lifetime and connectivity of M2M networks with sink mobility (for load balancing). Energy-efficient shortest-path routing (SPR) based networking mechanisms were comprehensively reviewed in the paper entitled ‘Energy efficient wireless unicast routing alternatives for machine-to-machine networks’ [32]. Energy-efficient unicast routing alternatives for sensor and adhoc networks were classified with a focus on additive link cost-based alternatives. However, the survey did not consider information collection-based (sensing) type of energy consumption [32]. Similarly, many of the routing techniques surveyed were designed for stationary nodes. Further survey can focus on scalability [32], protocol designs for mobile nodes, and topology dynamics. This work has been referenced in [31], which we reviewed in this paper, and [174] presented power efficient schemes for mobile adhoc network (MANET).
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7.2. Reliability Reliability refers to the timely and effective transport of the required data for its target applications. In other words, it defines the quantity of sent packets that ought to reach its destination within the required delay bound [175]. It is essential to mention that, the amount of data required to ensure reliability is application dependent. In traditional sensor networks, this could be achieved either by packet re-transmissions or recovering lost bits within a packet using coding schemes. Retransmissions result in additional overhead due to transmissions. This could cause network congestion and waste energy of sensors with constrained energy resources. The second approach achieves
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reliability and reduces transmission overhead since lost or corrupted bits within a packet are corrected [176]. Without assurances of reliability, concerned entities may be disinterested in the potential of M2M communication. Reliability is pivotal to achieving green M2M because misleading reports, prolonged delays, and data loss can occur because of inaccurate sensing, processing, and transmission [2]. For example, in applications very sensitive to latency such as alarms for intruder detection, if the alarm response is not timely, the intruder might leave the vicinity of the event unnoticed. Structural health monitoring requires long-term functional networks. In such applications, energy-aware routing algorithms, which consider residual energy levels for maximising network lifetime, are necessary [32]. For some critical monitoring applications, packet retransmissions may severely decrease network lifetime, and therefore, retransmission-aware energyefficient routing algorithms can be advantageous [32]. Reliability can be improved by exploiting redundant technologies such as information and spatial and temporal redundancy. Although, redundancy is an effective solution, it comes with additional cost [2]. In industrial automation systems where a hybrid of wired and wireless architecture may be required, achieving the target reliability may pose challenges. This can be approached using QoS aware schedulers. For instance, the solution proposed in [175] can be adapted to suit M2M applications with diverse delay bounds in these environments. Balancing energy-efficiency and reliability remains an open issue in M2M communication.
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Relevant Literature Lu et al. [2] presented major technical requirements for emerging M2M communication in the article entitled ‘GRS: The Green, Reliability, and Security of Emerging Machine-to-Machine Communications’. A scheme for energy efficiency in M2M communication was provided with a discussion on several alternatives for ensuring high-level reliability and security. However, GRS issues were only discussed in a general context. According to the authors, it is necessary to identify and address GRS issues for several existing and upcoming M2M applications. A few notable papers that have referred to this work include [7, 11, 22], which we have considered in this survey and [177, 178, 23, 179, 181]. Reference [177] proposed an aggregation scheme for preserving privacy in smart grids while [178] addressed security concerns for 5G using a lightweight 39
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message authentication scheme. [23] concentrated on M2M communication in vehicular networks, [179] extended Fog computing3 for distributed decentralised smart building management, identifying issues yet to be studied. [181] presented technologies, challenges, and foresights concerning energyefficient IoT.
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7.3. Security Network security refers to the mechanisms put in place to ensure confidential, undefiled and trustworthy transfer of information. As such, there should be an assurance of confidentiality, integrity and non-repudiation of data transfer within the network [182]. Security issues can hinder the growth of M2M and some of its applications as considerable personal data can be ‘stolen’ from M2M devices when compared to personal communication devices. M2M is also characterised by existing threats in data communication. These threats can be classified as physical, logical, and data attacks. Physical attacks include theft, modification of software, and side-channel attacks. Logical attacks include impersonation, denial of service [183], and relay attacks [27]. Data attacks include privacy, data alteration, and selecting forwarding attacks. M2M security concerns also include trust creation, advanced credential management for mobile communication, and horizontal end-to-end security solutions [27]. In cellular networks, M2M deployed in UDNs poses security concerns such as privacy issues. Such issues are attributable to the heterogeneous network structure and the ‘frequent’ handovers that exist in such networks. Security should be considered from the outset of M2M application development in a holistic manner as general requirements may differ from application-specific requirements. An example is the difference between telemetry-based e-Health body area networks and home area networks in terms of battery life and the number of devices [10]. Another important consideration is interoperability because the network generally consists of several protocols and heterogeneous capacity. Schemes using dynamic configuration and adaptive protocols for end-to-end security can be deployed to address this issue. M2M data must be secured from source to destination using hop by hop or end-to-end security [27]. Other considerations include [33]: 3
The Fog extends the Cloud by bringing it closer to the devices which produces data. This minimizes latency and retains sensitive data within the network [180].
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• Addressing issues related to mobility and delay-sensitivity. Proposed schemes should be robust to ensure that M2M communication is resilient against attacks;
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• Designing secure and scalable key management schemes;
• Ensuring mobility in security schemes for data origin authentication;
• Proposing robust lightweight and highly efficient cryptographic mechanisms;
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• Addressing entity authentication with minimal computation for devices having limited resources;
• Ensuring that privacy-preserving schemes consider the trade-off between delay, robustness, and resource constraints; • Addressing security issues associated with availability and group key management for multicast communication.
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Relevant Literature Latvakoski et al. [27] presented a review of M2M information and services in the paper ‘A Survey on M2M Service Networks’. The focus of this paper is on communication, security, and service technologies for M2M. The authors evaluated the effectiveness of technologies for addressing M2M service network issues. Reference [27] reviewed several security technologies related to Local Area Network (LAN) device domain. This article is referenced in [184], which surveyed the pros and cons of wireless technologies in home networks. The survey on M2M security entitled ‘M2M Security: Challenges and Solutions’ focused on critical issues for achieving secured M2M communication and preventing relevant attacks. The outstanding feature of this paper is that general M2M challenges such as scalability, heterogeneity, and resource constraints were discussed in the context of lapses in security. Future works should consider the issue of physical attacks as this paper mainly focused on logical and data attacks. Articles that have referred to this work include [185, 186, 187]. 41
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8. Conclusion
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Authors in [185] proposed a novel key management security protocol. This is was done to achieve maximal airtime savings in modern devices by using implicit certificates and Deffie-Hellman exchange. Reference [186] studied the effectiveness of current protocols and network stacks for IoT security. [187] proposed a scheme that recommends services for users of connected objects. Tuna et al. [34] surveyed security threats and potential solutions to minimise the impact of such threats or to mitigate the threats in M2M networks. This was presented in ‘A survey on information security threats and solutions for machine to machine (M2M) communications’. Consequently, the authors identified further research opportunities and challenges. There have been several recent references to Tuna et.al, including [188, 189]. Authors in [188] used the principles of blockchain technology to design a sophisticated blockchain structure for M2M communication based on a case study involving cotton spinning production for demonstration and validation. [189] proposed an authentication scheme suitable for multi-domain M2M scenarios. In addition to its authentication property, the scheme achieves anonymity by using a hybrid of certificateless cryptography and advanced encryption standards. It was shown to be effective against several security attacks such as Denial of service, impersonation, and replay and man-in-themiddle attacks.
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M2M communication has become a promising communication paradigm that would impact human lives in the years to come. This is because machine devices would communicate autonomously, thereby rendering interesting services to humans. Efforts are being made in academia and industry to ensure that the large number of machines involved in autonomous communication are well supported from several domains and there have been numerous articles on this matter. In this survey, we approached open questions in a particular way by classifying prime references in this area into themes and then discussing their fundamental concepts. Then potential areas for future work (some of which are summarized in Figure 8) were highlighted based on each theme. This is intended to present an overview of research opportunities available in these aspects. Relevant references for understanding such issues in greater depth were also reviewed with insights into their significant contributions and (or) limitations. More research and surveys that have spurred from these refer42
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Figure 8: Summary of some issues highlighted
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ences are highlighted with the aim of familiarising readers with some of the recent developments. Specifically, in this paper, we learn that one of the most crucial aspects of M2M communication is supporting the large number of machine devices with their diverse QoS requirements at the MAC layer. Other aspects include the proper choice of technology to support these devices and ensuring interoperability in terms of standards, service platforms, and architecture. It is important to cite that proper support for mobility, network densification, and gateways with cognitive capabilities is desirable. Reliable and secure solutions should be incorporated into the architecture of M2M while also considering energy efficiency. Looking into recent trends in wireless communication literature [137, 190, 191, 192, 193, 194, 195, 196, 197], it can be observed that advances in transportation, health, agriculture, manufacturing, and industry will present new challenges and further research opportunities for M2M communication. The ubiquitous use of autonomous vehicular communication is set to revolutionise the current transportation systems. Manufacturing will require more automated interactions of machines with the physical environment i.e cyberphysical systems. Critical health applications would require ultra-low latency M2M communication with ultra-reliable device connections. Smart drones and autonomous farm machines will also be able to work on large plots of land thereby reducing human effort. To realise these level of reliability and automation, several new technologies are expected to permeate the development of M2M communication. These include: edge computing, fog computing, and network slicing. Through edge computing, computational devices are brought closer to machine devices which would help mitigate traffic congestion, reduce latency in data exchange, improve the response time in real-time applications and improve the battery life of energy-constrained machine devices. Fog computing would enable machine devices to connect to fog clusters thereby facilitating proximity based M2M applications. Network slicing allows a physical infrastructure to accommodate several network instances in form of a virtual network architecture which is highly propitious for ultra-reliable and low-latency M2M communication. In the lower layer, network-coded multiple access (NCMA)4 and universal 4
a non-orthogonal multiple access scheme which uses non-orthogonal codewords for
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filtered multi-carrier (UFMC)5 are suitable for future advancement in M2M communication. NCMA is suitable for massive number of machines having small packets of data to transmit. This has the potential of improving the throughput, connectivity and, performance of M2M networks. Furthermore, it can reduce collision probability in contention based multiple access. UFMC is suitable for applications with short-bursts of traffic. Autonomous relay-assisted UAV communication, where UAVs can connect to terrestrial networks through relays, are also expected to find promising applications in the future. Asides the aforementioned, it is reasonable to expect that advances in M2M communication will also be driven by 6G expectations [199]. This would require advancements in technologies such as wireless charging and energy-harvesting. Current research [200, 201, 202, 203, 204, 205, 206, 207, 208] also shows that NB-IoT would highly impact M2M research in years to come thereby providing further opportunities. Acknowledgements
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The authors would like to appreciate everyone who gave comments and provided support to improve the content, quality and presentation of this paper. This work has been supported by the Malaysian Ministry of Higher Education under the Malaysian International Scholarship scheme. This publication is also supported by the Malaysian Ministry of Education under Research Management Center, Universiti Putra Malaysia, PUTRA Grant with High Impact UPM/700-2/1/GPB/2017/9557900.
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Table 1: Some key abbreviations used in this paper
Abbreviation
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3GPP 5G ACB BS CAN CN
Meaning 3rd Generation Partnership Project 5th Generation wireless systems Access Class Barring Base Station Controller Area Network Core Network
resource spreading [195, 198] 5 an alternative to orthogonal frequency division multiplexing [196]
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Table 1: Key Abbreviations (continued)
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Cyber Physical Systems Cognitive Radio Networks Device-to-Device Distributed Antenna System Distributed Queuing Evolved Node B Evolved Packet Core Evolved Universal Terrestrial Radio Access European Telecommunications Standards Institute General Packet Radio Service Global System for Mobile Communications Human-to-Human Internet of Things Internet of Vehicles Intelligent Transport System Local Area Network Low Power Wide Area Long-Term Evolution Long-Term Evolution Advanced LTE in unlicensed spectrum Medium Access Control Machine-to-Machine Multiple-input and Multiple-output Message Queueing Telemetry Transport Machine Type Communication Machine Type Devices On Board Unit Open Geospatial Consortium Peer-to-Peer Physical layer Physical Resource Blocks Physical Random Access Channel Quality of Service Random Access
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CPS CRNs D2D DAS DQ eNB EPC E-UTRA ETSI GPRS GSM H2H IoT IoV ITS LAN LPWA LTE LTE-A LTE-U MAC M2M MIMO MQTT MTC MTD OBU OGC P2P PHY PRBs PRACH QoS RA
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Table 1: Key Abbreviations (continued)
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Random Access Channel Radio Access Network Radio Access Technology Radio Frequency Identification Radio Remote Head Serving Gateway Small cell Base Station Service Capability Layer Standard Development Organisation Smart Utility Networks Sensor Web Enablement Time Division Multiple Access Ultra Dense Networks User Equipment Ultra-Wide Band Vehicular Adhoc Networks Vehicle-to-Vehicle Vehicle-to-Infrastructure Wireless Access to Vehicular Environment Wireless Fidelity Wireless Local Area Networks Wireless Sensor Networks
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RACH RAN RAT RFID RRU S-GW SBS SCL SDO SUNs SWE TDMA UDNs UE UWB VANET V2V V2I WAVE Wi-Fi WLAN WSN References
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Biography
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Oluwatosin Ahmed Amodu received his Bachelor of Technology degree in Electrical Electronics Engineering from the Federal University of Technology Akure, Nigeria 2012. He completed his Masters degree in Computer Science with a specialization in distributed computing at Universiti Putra Malaysia 2016. He is currently pursuing a PhD Programme in Wireless Communication and Network Engineering. His research interest lie in sensor networks, machine type communications, device-to-device communication, spectrum sharing networks and stochastic geometry.
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Mohamed Othman received the Ph.D. degree (Hons.) from the National University of Malaysia. He is currently a Professor in computer science with the Department of Communication Technology and Network, Universiti Putra Malaysia (UPM). Prior to that he was a Deputy Director of the Information Development and Communication Center, where he was in charge of UMPNet network campus, uSport Wireless Communication Project, and 72
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the UPM DataCenter. He is also an Associate Researcher and a Coordinator of high speed machine with the Laboratory of Computational Science and Informatics, Institute of Mathematical Science, UPM. In 2017, he received an Honorable Professor from South Kazakhstan Pedagogical University, Shymkent, Kazakhstan, and also was a Visiting Professor with South Kazakhstan State University, Shymkent, and L. N. Gumilyov Eurasian National University, Astana, Kazakhstan. He published more than 300 International journals and 330 proceeding papers. His main research interests are in the fields of computer networks, parallel and distributed computing, highspeed interconnection networks, network design and management (network security, wireless and traffic monitoring), consensus in IoT, and mathematical model in scientific computing. He is a member of the IEEE Computer Society, the IEEE Communication Society, Malaysian National Computer Confederation, and Malaysian Mathematical Society. He was a recipient of the Best Ph.D. Thesis in 2000 by Sime Darby Malaysia and Malaysian Mathematical Science Society. He has also filed six Malaysian, one Japanese, one South Korean, and three U.S. patents.
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