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An IoT-based smart cities infrastructure architecture applied to a waste management scenario
Ad Hoc Networks 87 (2019) 200–208
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An IoT-based smart cities infrastructure architecture applied to a waste management scenario Patric Marques, Diogo Manfroi, Eduardo Deitos, Jonatan Cegoni, Rodrigo Castilhos, Juergen Rochol, Edison Pignaton, Rafael Kunst∗ Informatics Institute Federal University of Rio Grande do Sul Av. Bento Goncalves, 9500 - Porto Alegre, RS - Brazil
a r t i c l e
i n f o
Article history: Received 6 March 2018 Revised 11 October 2018 Accepted 16 December 2018 Available online 28 December 2018 Keywords: Internet of things Smart cities Energy efficiency Intelligent waste management Wireless communications
a b s t r a c t Studies estimate that by 2050 two thirds of the world population will be leaving in urban areas, what leads to the necessity of intelligent services to meet the needs of the cities residents. An emerging solution to deal with this scenario is the convergence of information and communication technologies through the implementation of the concepts of smart cities and Internet of Things to provide solutions in diverse fields like infrastructure, transportation, and surveillance. Considering this challenging scenario, in this article a multilevel IoT-based smart cities infrastructure management architecture is proposed and the waste management problem is used as a case study to evaluate the performance of the proposed solution. Results proved the concept of the architecture, showing that it is able to manage up to 3902 garbage bins simultaneously. These bins are able to correctly separate organic and recyclable waste in both indoor and outdoor scenarios, presenting low response times, what leads to a good quality of experience to the users of the system. © 2018 Elsevier B.V. All rights reserved.
1. Introduction The United Nations estimate that by 2050 almost two thirds of the world’s population will be living in urban areas, increasing the already high population density of big cities [1]. With the increase of the urban population, the development of infrastructure and services will become indispensable to meet the needs of the cities residents [2]. An emerging solution to deal with this scenario is the convergence of information and communication technologies through the implementation of the concept of smart cities. This concept is based on the idea of using Internet of Things (IoT) sensors and devices to intelligently implement solutions that meet the demands generated by this expected scenario [3]. These future urban areas will demand solutions in diverse fields, including city services infrastructure, transportation, surveillance, and technology related issues. The efficient management of these kinds of services has a significant impact on the quality of life of the citizens [4]. Considering this challenging scenario, the implementation of the IoT concepts becomes mandatory for smart cities, since it allows objects to connect with each other and interact with humans
∗
Corresponding author. E-mail addresses: [email protected] (P. Marques), [email protected] (E. Deitos), [email protected] (J. Cegoni), [email protected] (R. Castilhos), [email protected] (J. Rochol), [email protected] (E. Pignaton), [email protected] (R. Kunst). https://doi.org/10.1016/j.adhoc.2018.12.009 1570-8705/© 2018 Elsevier B.V. All rights reserved.
in a pervasive and intelligent way [5]. One of the services which is becoming important in this context is the efficient management of the waste generated in big cities. Several works propose efficient solutions for intelligent garbage collection using the concepts of IoT. Shyam et al. [6] developed an IoT-based system that measures the level of waste in residential waste bins and sends this data to a server, aiming at improving garbage collecting routes in big cities. The system proposed by Bharadwaj et al. [7] implements LoRa communication technology to notify the collection systems when waste bins are full. Hong et al. [8] presented a successful IoTbased system for waste control which is currently implemented in South Korea. The main concept behind the proposal is that at the time of disposal, residents are identified by RFID cards in waste bins. The waste is weighed and the information is sent to a server that automatically processes this information for billing purpose. Although very relevant, the proposals currently found in the literature are mainly focused on garbage collection, not taking into account another important aspect, which is the correct waste separation considering the characteristics of the disposed products. Taking into account this unsolved problem, in this article a multilevel IoT-based smart cities infrastructure management architecture is proposed and the waste management is used as a case study to evaluate the performance of the proposed solution. The multilevel approach allows the integration of physical objects, communication infrastructure, cloud platform, and IoT-based services in a perva-
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sive way, what facilitates the implementation of diverse kinds of services in the context of smart cities. The main goals and contributions of the proposed solution are presented as follows. • Modular design, allowing independent and simultaneous execution of the different layers of the architecture to provide support to multiple protocols and services; • To easily integrate devices and cloud services under different communication network protocols; • Low power consuming solution, allowing the IoT devices battery to last longer; • Communications network quality of service (QoS) metrics are taken into account to guarantee that the response times are acceptable; • Evaluation of the performance of the proposed solution considering different communication protocols in real world waste separation scenarios. The proposed architecture is implemented using a Raspberry Pi hardware and is evaluated considering a case study of intelligent waste management. This case study considers two real world scenarios: (I) an indoor implementation to evaluate the behavior of the solution in a typical house, and (II) an outdoor scenario, where garbage bins equipped with the proposed solution are available in a big city park. In both situations, the proposed architecture is able to correctly separate the waste accordingly to the characteristics of the disposed products. Another concern of the proposed solution is to guarantee the confidentiality of the system users, therefore, three different protocols are evaluated to implement secure network communications: Message Queuing Telemetry Transport Protocol (MQTT), Constrained Application Protocol (CoAP), and Secure Hypertext Transport Protocol (HTTPS). The performance of each protocol is evaluated considering both power consumption and QoS-related metrics in order to identify the best one for implementation in indoor and outdoor scenarios. The remainder of this article is organized as follows. In Section 2, background aspects on IoT-based waste management are provided considering the related works currently found on the specialized literature. The proposed architecture is presented and discussed in Section 3. The evaluation methodology and the results obtained from the real world implementation of the proposed solution are presented in Section 4. Conclusions and directions for future investigations are provided in Section 5. 2. Background on IoT-based waste management Among several IoT-based services provided in smart cities, one of primary importance is the waste management. Dealing with this kind of service is becoming challenging due to the fast growing pace of the metropolitan areas of big cities. An emerging approach to provide efficient waste management in this scenario is to use Radio Frequency Identification (RFID) technology to help classifying the kinds of disposed products. This classification relies also on creating and maintaining databases to store characteristics of a large amount of products. Therefore, storage and processing of the information related with these products is often conducted in cloud environments, what creates another challenge related to providing QoS-enabled communication with the cloud. Considering the growth in the urban population and the consequent increasing demands for intelligent services as waste management, many IoT-based solutions have been presented in related works. Shyam et al. [6] reports the development and simulation of an intelligent mechanism to improve waste management in big cities. The proposed system is based on a geographic information system, which is combined with optimization algorithms. Comparisons are performed to evaluate the efficiency of a traditional
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static collection model compared to the proposed dynamic IoTbased garbage collection. Despite proposing a relevant solution, no details regarding the network infrastructure and its performance are provided. Bharadwaj et al. [7] propose a system that identifies the status of the waste bins. The system is able to calculate routes aiming at optimizing the resources used for garbage collection in cities. The proposed solution relies on LoRa Wireless Sensor Networks standard for communication purpose. The solution proposed by the authors makes use of the Google direction Application Programming Interface (API) to calculate routes. The main shortcoming of this related work, compared with the solution proposed in this article is that problems related to the separation of the products to be disposed are not considered in the presented solution. Hong et al. [8] present a solution in which RFID readers are installed in the waste bins to identify the individuals who are discarding waste in each bin. The system uses the collected information along with the weight of the discarded bin to feed a billing system. The waste bins are distributed at various locations within the city and are inter-connected using a mesh wireless network topology. The analysis of the related works provided evidence that despite intelligent IoT-based solutions have been proposed to deal with the waste management study case, there is a lack of evaluations of solutions implemented in the real world. Moreover, communication protocols are studied, but generally without taking into account important aspects like scalability and performance considering QoS metrics. Table 1 summarizes the features covered by related work in comparison with the solution proposed in this article. 3. Proposed architecture The architectural design of the solution proposed in this article brings together the concepts of Cyber Physical Systems (CPS) [9], advanced data communication systems [10], and embedded intelligence [11] to deal with smart cities related challenges. In order to allow the convergence of these concepts, a multilayer approach is defined to allow both independent and simultaneous operation of diverse features of the architecture. Fig. 1 depicts the proposed architecture. The proposed architecture is organized considering the existence of four layers: (I) Physical Objects, (II) Communication, (III) Cloud Platform, and (IV) Services. The first layer aims at making possible to IoT sensors to collect data that will feed the smart city architecture with information used to offer services to the population. After the sensors collect data, a communication device, which can implement different technologies, such as RFID, Bluetooth, and Zigbee, is used collect sensors data. This data is processed by a NodeMCU, which communicates with a local processing unit, responsible for gathering information used by the application which is providing a service. The local processing implemented in the Physical Objects layer brings elements of edge computing [12], as it pushes part of the computation to edge nodes, instead of relying in concentrating all the computation in a centralized remote server, for instance. Compared to similar architectures described in [12], the architecture here proposed provides additional security features for this type of network part, usually composed of resource constrained nodes, which are not explored in the [12]. Another comparable approach that provides a case study applying an edge computing algorithm integrated to an IoT mesh network in the context of a smart building system integrated is presented in [13]. Despite the similar idea of pushing part of the computation to the edge, the authors in [13] are not concerned neither with security, nor with performance aspects, as explored in this proposal. Some applications demand
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P. Marques, D. Manfroi and E. Deitos et al. / Ad Hoc Networks 87 (2019) 200–208 Table 1 Comparison between the proposed approach and related work. Protocols Shyam Bharadwaj Hong Proposed Solution
Ad Hoc Network LoRa Wireless Mesh Network CoAP, HTTPS, and MQTT
Theoretical
Protocols Analysis
RFID
Realistic Scenario
Scenarios
QoS
Power
X
X X X X
Outdoor Outdoor Outdoor Indoor and outdoor
X
X
X X
X X
Fig. 1. Architecture Design.
high computation power and/or the storage of large amounts of data. To provide the infrastructure for these specific applications, the proposed architecture facilitates access to a cloud platform that is responsible for providing compute engine and data storage services. IoT sensors are physical objects designed to execute different kinds of tasks and consequently collect various types of data. This characteristic of the IoT devices usually leads to variable amounts of data that need to be transmitted using different network technologies. The network technology to be used is defined considering both the amount of data to be transmitted and the physical implementation of the IoT device. Therefore, from the point of view of providing the infrastructure necessary to accommodate the sensors used to provide services in the context of smart cities, a variety of network technologies must be supported by the proposed architecture. To deal with different network access technologies, the proposed solution defines a communication layer that supports the implementation of various wireless technologies. The definition of the technology to be used is a responsibility of the local processing unit, which is located in the Physical Objects Layer and relays data to the communication layer using the interface of a network access point. This layer provides communications among all layers of the architecture.
The third layer of the proposed solution is the Cloud Platform, designed to provide three kids of services: processing, database queries, and data storage. Each of these services can be allocated dynamically to meet the requirements of different kinds of applications in the context of smart cities service provisioning. Although cloud solutions are very common nowadays, it is important to emphasize that not every type of applications and services require a cloud platform to operate properly. Considering this scenario and also that one of the design goals of the proposed architecture is to be generic enough to support any kind of service, this layer is always offered as part of the infrastructure provided by the proposed solution, however, its implementation is optional. In situation in which the cloud platform is not required, the local processing unit, located in the physical objects layer becomes responsible for data processing, storage and database operations. Another important feature of the architecture is the flow of information. Special attention is given to the fact that in the implementation of smart cities related services, a considerable amount of personal information is generally necessary for the applications to work properly. Due to the sensitivity of this kind of information, implementing solutions to guarantee the confidentiality of the transmitted data is of paramount importance. To deal with the confidentiality related challenges, the proposed solution supports
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different secure protocols that apply the concepts of cryptography to provide secure communications even when the transmissions pass through insecure channels, what is the case of commercial wireless networks. Examples of protocols supported by the proposed architecture are MQTT, CoAP, and HTTPS [14]. Aside from the secure communications protocols, a flow of information and interfaces are defined to allow data exchange among the different levels of the architecture. Specifically, in the physical objects layer, a flow of sensors data is defined to feed the local processing unit with information. Moreover, the cloud platform and the service layer have application and control data flows, respectively. Smart city related applications, in the proposed architecture, are located in the services layer. This layer implements four groups which are called classes of services: (I) Surveillance, (II) Transportation and Logistics, (III) Infrastructure, and (IV) Technology. In each class, different kinds of applications can be implemented to deal with the challenges of smart cities. It is important to emphasize that the proposed architecture is a generic solution, so the underlying layers are designed to offer support to the applications and therefore can be adapted to the specific implementation of a given service. Considering this characteristic of the proposed architecture, in the next section, a case study of intelligent waste management is presented considering an adaptation of the generic architecture applied to deal with a real world problem. 4. Case study and performance evaluation In order to evaluate the proposed architecture, this article considers a case study involving an IoT-based waste management system. The adaptations of the architecture to the case study are presented in 4.1. The results are presented and discussed in 4.2. 4.1. Waste management case study This section describes a case study consisting of an IoT-based waste management system that systematically collects information regarding the kinds of products to be disposed in order to identify and indicate the correct destination of each product. In the case study, the proposed architecture is adapted to focus on the specific application of waste management. Fig. 2 presents a specific version of the architecture, already adapted to meet the requirements of the case study. The sensors, in the physical objects layer, are represented, in this case study, by garbage bins equipped with RFID readers, which are designed to collect data from tags located in the products to be disposed off. These tags provide the identification of the product. The data collected by the RFID readers is processed by a Raspberry Pi hardware, which is responsible for coordinating the communication with the databases located in a cloud server, using an IEEE 802.11 device to access the Internet. It is important to highlight that the proposed solution supports other technologies for Internet access, but IEEE 802.11 is flexible enough to operate in both indoor and outdoor scenarios. The implementation of a cloud solution is justified due to the amount of products that need to be registered for the solution to work properly, i.e. to allow the identification of which product is being disposed and indicate the correct garbage bin to be used. Moreover, every disposed product is registered to allow the city administration to create a historical database that can be used to constantly evaluate and improve the garbage collection routes, based on the amount and kind of disposed products. An important concern of the proposed solution is data confidentiality, since the waste disposed by an individual or a family usually contains sensitive personal information. To deal with the confidentiality related issues, in the case study, three secure protocols are evaluated: HTTPS, CoAP, and MQTT. The selection of such
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protocols is based on related works that have conducted theorectical analysis of these protocols ([14], [15], [16]), but were not focused on the evaluation of a real world implementation. Moreover, HTTPS was chosen because it is a well-known protocol, which is widely implemented in Internet-based applications and thus can be easily adapted to the proposed architecture. On the other hand, CoAP and MQTT are recently proposed protocols, designed to deal specifically with IoT-based applications and therefore are considered very relevant in the context of the proposed case study. The implementation of the architecture in a realistic scenario considers the following work flow to guide the users of the system to the correct disposal of products. When a person approaches the garbage bins, RFID readers installed in the bins communicate with a RFID tag located in the container of the product. This information is processed by a Rasberry Pi hardware, which queries the products database (in the cloud platform) to identify the kind of product to be disposed and consequently open the correct bin according to the nature of the product to be disposed (organic or the type of recycle garbage). After the disposal, information about the product, such as its name, type, and weight are uploaded to the historical database, located in the cloud, along with the location of the garbage bin. It is important to note that a proximity sensor installed next to the garbage bins activates the system only when it is necessary, aiming at reducing power consumption. The evaluation of the proposed architecture considers two scenarios. The first one represents the management of waste inside residences in an indoor environment. The second one considers an outdoor environment, in which garbage bins equipped with the system are installed in a public park located in a big city. The residential scenario is presented in Fig. 3 (a). In this case, two garbage bins are available, one for organic waste and another for recyclable product containers. The experiments performed in this scenario consider the usage of the bins in three periods during a day, morning, midday, and evening to represent the profile of the residents of a typical home, i.e. waste generated during breakfast, lunch, and dinner. The second scenario is designed to evaluate the performance of the system in a public area, as depicted in Fig. 3 (b). This scenario considers four different types of garbage bins, one for organic waste and three for different kinds of recyclable waste, i.e. paper, glass, and plastic. In this scenario, the expected number of message exchanges is larger than in the residential scenario. This behavior is expected because in this scenario the waste disposal depends on the amount of people in that given public place along the day. For the sake of the experiment, it is considered that a waste disposal occurs every 15 minutes, following a random selection of products. In technical terms, the deployment of the solution considers that each garbage bin is equipped with a MF RC522 RFID reader manufactured by NXP. This is a low power consuming hardware that supports both read and write operations, communicating at 13.56MHz frequency. The specification of this RFID reader considers ISO 14443A standard and provides three connection interfaces: SPI, I2C, and serial UART [17]. In the proposed solution, the reader is connected to a ESP-12F NodeMCU module, which is a Wi-Fi Development Kit manufactured by Espressif Systems. This kit was selected because it is a low cost open source WiFi module typically used for the implementation of IoT-based applications. The local processing unit is implemented using a Raspberry Pi 3 Model B platform. The Raspberry Pi is a low cost, low power demanding, single board computer, which can handle multiple functions. It is equipped with a 1.2Ghz 64-bit quad-core processor. This Raspberry Pi board has a built in module which implements IEEE 802.11n standard [18], which was used for WiFi based Internet access, implemented in the proposed solution to communicate with the cloud platform. Table 2 summarizes the main characteristics of the scenarios considered for performance evaluation.
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Fig. 2. Case Study Architecture.
Fig. 3. Study Case Scenarios.
4.2. Results and discussion In this subsection the results obtained from the real world implementation of the proposed IoT-based waste management case study are presented and discussed. The basic configuration of the
experiments consider 100 waste disposal in each garbage bin for each evaluated scenario and protocol configuration. It is also important to emphasize that for the residential scenario, the disposals occur at a lower rate compared to the public park scenario, due to the modeled used behavior, which is concentrated in three
P. Marques, D. Manfroi and E. Deitos et al. / Ad Hoc Networks 87 (2019) 200–208 Table 2 Scenarios deployment characteristics.
Environment Recycle Garbage Bins Organic Garbage Bins Communication technology Network Layer Local processing unit CoAP implementation HTTPS implementation MQTT implementation
Scenario 1: Residence
Scenario 2: Public Park
Indoor 1 1 RFID WiFi Raspberry PI Microcoap server OpenSSL and Apache Mosquitto Broker
Outdoor 3 1
Table 3 Electric current consumed by NodeMCU and RFID reader. Device
Mode
Electric Current (mA)
NodeMCU - IEEE 802.11 NodeMCU - IEEE 802.11 MFRC 522 - RFID reader MFRC 522 - RFID reader
Operation Sleep Operation Sleep
74.523 4.851 16.012 1.413
specific periods of the day. Three main approaches are considered to evaluate the proposed architecture considering the waste management case study. First, results related to the power consumption are presented. The second kind of results are related to the QoS guaranteed in network transmissions. In this sense, latency, jitter, and throughput metrics are evaluated. Finally, the amount of garbage bins supported by each kind of protocol is studied taking into account the implementation of HTTPS, MQTT, and CoAP. Consuming low amounts of power is of paramount importance in an IoT-based scenario to increase the battery life of the sensors. In this specific case study, the goal is to evaluate the energy consumed by the devices in situations where HTTPS, MQTT, and CoAP protocols are implemented. It is important to note that the electric current consumed by the NodeMCU is measured separately from the current demanded by the RFID reader. This approach guarantees that the energy consumption considered for evaluation purposes only depends on the performance of the protocol and is not dependent on the random behavior of RFID cards reading. Both the NodeMCU and the RFID reader have two modes of operation: sleep mode and operation mode (or non-sleep). Regardless of which protocol is implemented in the NodeMCU, the measured values of electric current do not change while the devices are in sleep mode. These values, however are changed when the device is configured to be used in the operation mode. The average electric current consumed in each configuration is shown in Table 3. The first analysis of this case study is based on Fig. 4, which plots the behavior of the electric current considering the implementation of CoAP, MQTT, and HTTPS in both operation and sleep modes. The presented data was acquired in one of the garbage bins in the outdoor scenario and represent the average energy consumption considering the implementation of different secure transmission protocols. The overall experiment took around 12 seconds, considering that each protocol was executed for about 4 seconds. Initially, each protocol is configured to start in sleep mode. The activation of the operation mode can be clearly observed in the graph presented in Fig. 4 by analyzing the peaks, which can be observed between the seconds 3 and 4 (HTTPS); 5 and 6 (CoAP); and 7 and 8 (MQTT). The reason for such occurrence is correlated to the existence of a led connected to the Reset pin of the NodeMCU, which is activated when the protocol state changes from sleep to operation mode. As can be seen in the figure, all protocols present similar behaviors in terms of electric current when the operational status of the architectural components is altered.
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Another analysis related to power consumption is conducted to correlate the amount of waste disposals with the power consumed by the proposed solution. This kind of evaluation is important to allow the assessment of the devices battery life. Considering the experimental parameters presented in Table 3, it is possible to calculate the power consumption of the devices in each operation mode. In the specific case study, the cost-benefit of enabling or not sleep mode is evaluated and the results are presented in Fig. 5. To evaluate the cost-benefit, the power consumption (E) is calculated following Eq. (1), where V represents the voltage supply of the NodeMCU, which is set to 5V. I is the electric current demanded by the IEEE 802.11 and t is the duration of the communication, which is set to 2129 ms in this experiment.
E = V × I × t
(1)
Considering the evaluated scenario, the implementation of sleep mode proves to be advantageous since it consumes less energy in all practical situations. Not implementing sleep mode would become an advantage only in situations where more than 90 discards are made in a period of 2129 ms, what corresponds to a disposal every 25 ms, configuring an unrealistic scenario. The second approach to evaluate the proposed architecture is related to QoS metrics. The first metric analyzed is the round-trip latency, considering the communication between the garbage bins located in both indoor and outdoor scenarios with the cloud platform. The QoS-related experiments were performed to evaluate the time demanded by the system to correctly identify the garbage bin to be opened considering the type of waste to be disposed. Guaranteeing a low latency is very important for this kind of implementation, since the users should not wait long times for a bin to open. The outcomes of the latency related experiments in the indoor scenario are presented in Fig. 6 (a), while the results regarding the outdoor scenario are shown in Fig. 6 (b). In both scenarios, the results reflect the average latency measured during the experiments. The first impression when analyzing the graph shows that all protocols provide relatively low latency, keeping the response times below 12ms in the indoor scenario and lower than 14ms in the outdoor scenario. Besides guaranteeing low response times, it is important to emphasize that in all experiments the correct bin was selected by the system. In most situations not implementing sleep mode provides faster responses, what is explained by the time demanded to restart the modules when sleep mode is implemented. However even in sleep mode, the latency is acceptable for real world implementations of the architecture. Therefore, considering the performance of each protocol and taking into account that the sleep mode consumes less power, it is possible to conclude that the best cost-benefit considering the latency metric in both indoor and outdoor scenarios is to implement MQTT with the sleep mode enabled. The average Jitter is the second QoS-related metric evaluated in this case study. This metric is calculated considering the variations on the latency of the communication when a disposal occurs. Analyzing Jitter is important for the analyzed scenarios because a low value guarantees that the response times are consistent in every disposal, what leads to quality of experience for the users of the waste management system. Results related to the Jitter values measured in the indoor scenario are presented in Fig. 7(a) and the outcomes of the experiments for the outdoor scenario are depicted in Fig. 7(b). Analyzing the results it is possible to observe that, in general, Jitter is higher in outdoor measurements, what is expected, since this is a less controlled scenario. Another noticeable behavior is that there is no significant variability in the Jitter when the operation mode (sleep or non-sleep) is changed. Therefore, considering the power consumption, the operation mode, and the different
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0.35 HTTPS CoAP MQTT 0.3
Current (A)
0.25
0.2
0.15
0.1
0.05
0 1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Time (s) Fig. 4. Electric current behavior.
300 Sleep Mode No Sleep
Energy Consumption [uWh]
250
200
150
100
50
0 0
20
40
60
80
100
Amount of waste discards Fig. 5. Power consumption x Amount of waste discards.
kinds of secure transmission protocols, MQTT configured to operate in sleep mode, is the one which provides the best cost-benefit according to this experiment. Network throughput is another QoS metric that affects the users quality of experience, since it impacts on the time required for a garbage bin to open for a given user to dispose the waste. In this case study, the throughput is measured using Wireshark to calculate the amount of data exchanged between the garbage bins and the cloud platform. The amount of bins is varied between 1 and 4 to reflect both indoor and outdoor scenarios. Moreover, the system is stressed to evaluate the maximum throughput that can
be attained after the implementation of CoAP, HTTPS, and MQTT protocols. The outcomes of these experiments are summarized in Table 4. The analysis of the results show that in the evaluated scenarios, HTTPS attains the highest throughput. Although this result is relevant, it was obtained in a limited scenario, designed to prove the concept of the proposed architecture. Therefore, to scale the solution to a more realistic scenario, it is also important to evaluate the maximum throughput of each protocol, obtained after stressing the system. In such situation, it is possible to conclude that MQTT protocol surpasses HTTPS, becoming the protocol that pro-
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14 No Sleep Sleep
12
12
10
10
Latency [ms]
Latency [ms]
No Sleep Sleep
8
6
8
6
4
4
2
2
0
0 CoAP
HTTP
MQTT
CoAP
HTTP
MQTT
Fig. 6. Latency Evaluation. 3
3 No Sleep Sleep
2.5
2.5
2
2
Jitter [ms]
Jitter [ms]
No Sleep Sleep
1.5
1.5
1
1
0.5
0.5
0
0 CoAP
HTTP
MQTT
CoAP
HTTP
MQTT
Fig. 7. Jitter Evaluation.
Table 4 Throughput Analysis.
Table 5 Amount of Supported Garbage Bins.
Garbage Bins
Throughput (bps) CoAP
HTTPS
MQTT
1 2 3 4 MAX
61 86 115 141 105,0 0 0
2830 5556 8201 11,0 0 0 91,0 0 0
142 411 607 819 110,0 0 0
Protocol
Number of Garbage Bins
CoAP HTTP MQTT
3902 33 494
Table 6 Cost-benefit Analysis Summary.
vides the best throughput considering a typical implementation of the solution in a big city. For the final analysis conducted in this article, the throughput data is extrapolated to obtain the expected amount of garbage bins supported by each analyzed protocol. In order to do that, a linear regression technique using the least squares method is applied to obtain the equation that describes the behavior of each protocol. This type of extrapolation is feasible as there is no factor that would change the deployed setup, besides the number of nodes. Following this rationale, the number of garbage bins distributed in a big city needed to bring the system to its limits for each protocol is calculated and presented Table 5. After analyzing all metrics, it is important to come to a conclusion regarding which protocol fits better to the scenarios evaluated in this case study. In order to do that, in Table 6, the protocol
Metric
Protocol/Mode
Power Consumption Latency Jitter Throughput Amount of Garbage Bins
Sleep Mode MQTT MQTT MQTT CoAP
which presents the best cost-benefit for each evaluated metric or operation mode is presented. As can be seen, in most situations, MQTT is highlighted as the best solution, however, CoAP has similar performance with the advantage of being more scalable and therefore, one can conclude that it is the protocol which provides the best results for the analyzed scenarios.
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5. Conclusion and future work This article proposed a multilevel architecture to support IoTbased smart cities systems. The goal of this proposal was to address the increasing demand for intelligent services in the continuous growing urban environments. As a case study, the article presented a waste management system to evaluate how the general architecture adapts to particular implementation that aim at solving specific smart cities related challenges. This case study was selected because waste management is an important problem in big cities and also provides the opportunity to explore at least two evaluation scenarios, one indoor and another outdoor. Based on these waste management scenarios, the architecture was implemented along with three different protocols designed to provide secure communication, namely CoAP, HTTPS, and MQTT. The resulting system was evaluated taking into account energy consumption, latency, Jitter, and throughput as evaluation metrics. Based on the acquired results, the scalability was also analyzed considering the impact of a growing number of concurrent garbage bins in the system. Results showed that CoAP is the protocol which supports the higher amount of concurrent users, guaranteeing the coexistence of up to 3902 garbage bins. In terms of power consumption, it was proved that sleep mode is recommended despite of the secure communication protocol which is being implemented. Finally, latency, Jitter, and throughput QoS related metrics were also evaluated. In this specific evaluation, MQTT obtained the best results, however CoAP also performed very well. Considering all the results obtained in a real world experiment, it is possible to conclude that CoAP provides the best cost-benefits, since it supports a higher amount of garbage bins while provides an acceptable level of QoS. This article proved a concept by implementing an architecture which allowed intelligent waste management in the context of smart cities. Although relevant results were obtained, there is still space for future investigations. In this sense, an interesting approach is to implement other protocols designed to operate in the context of IoT systems, such as AMQP and XMPP. Another important analysis would be to consider the implementation of other network layer technologies, like 5G, LTE-Advanced, IEEE 802.22, and Licensed Shared Access to improve even more the QoS offered to the system users. Finally, a very important future work includes the implementation of the solution in a larger scale, involving, for example celebrating an agreement with a city administration focusing on increasing the amount of public spaces where the system is implemented. References [1] World Urbanization Prospects. 2014 Revision, Technical Report, 2014. United Nations, Department of Economic and Social Affairs http://www.un.org/en/ development/desa/publications/2014-revision- world- urbanization- prospects. html.
[2] H. Arasteh, V. Hosseinnezhad, V. Loia, A. Tommasetti, O. Troisi, M. Shafiekhah, P. Siano, Iot-based smart cities: a survey, in: 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 2016, pp. 1–6, doi:10.1109/EEEIC.2016.7555867. [3] T. hoon Kim, C. Ramos, S. Mohammed, Smart city and iot, Future Gener. Comput. Syst. 76 (2017) 159–162, doi:10.1016/j.future.2017.03.034. [4] T. Anagnostopoulos, A. Zaslavsky, K. Kolomvatsos, A. Medvedev, P. Amirian, J. Morley, S. Hadjieftymiades, Challenges and opportunities of waste management in iot-enabled smart cities: a survey, IEEE Trans. Sustainable Comput. 2 (3) (2017) 275–289, doi:10.1109/TSUSC.2017.2691049. [5] R. Kunst, L. Avila, E. Pignaton, S. Bampi, J. Rochol, Improving network resources allocation in smart cities video surveillance, Comput. Netw. 134 (2018) 228– 244, doi:10.1016/j.comnet.2018.01.042. [6] G.K. Shyam, S.S. Manvi, P. Bharti, Smart waste management using internet-ofthings (iot), in: 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), 2017, pp. 199–203, doi:10.1109/ICCCT2.2017. 7972276. [7] A.S. Bharadwaj, R. Rego, A. Chowdhury, Iot based solid waste management system: a conceptual approach with an architectural solution as a smart city application, in: 2016 IEEE Annual India Conference (INDICON), 2016, pp. 1–6, doi:10.1109/INDICON.2016.7839147. [8] I. Hong, S. Park, B. Lee, J. Lee, D. Jeong, S. Park, IoT-based smart garbage system for efficient food waste management, Sci. World J. 2014 (2014), doi:10.1155/ 2014/646953. [9] J. Lee, B. Bagheri, H.-A. Kao, A cyber-physical systems architecture for industry 4.0-based manufacturing systems, Manuf. Lett. 3 (Supplement C) (2015) 18–23, doi:10.1016/j.mfglet.2014.12.001. [10] M. Wollschlaeger, T. Sauter, J. Jasperneite, The future of industrial communication: automation networks in the era of the internet of things and industry 4.0, IEEE Ind. Electron. Mag. 11 (1) (2017) 17–27, doi:10.1109/MIE.2017.2649104. [11] J. Wang, Y. Sun, W. Zhang, I. Thomas, S. Duan, Y. Shi, Large-scale online multitask learning and decision making for flexible manufacturing, IEEE Trans. Ind. Inf. 12 (6) (2016) 2139–2147, doi:10.1109/TII.2016.2549919. [12] M. Satyanarayanan, The emergence of edge computing, Computer (Long Beach Calif) 50 (1) (2017) 30–39, doi:10.1109/MC.2017.9. [13] A. Gajjar, Y. Zhang, X. Yang, A smart building system integrated with an edge computing algorithm and iot mesh networks: Demo abstract, in: Proceedings of the Second ACM/IEEE Symposium on Edge Computing, in: SEC ’17, ACM, New York, NY, USA, 2017, pp. 35:1–35:2, doi:10.1145/3132211.3132462. [14] N. Naik, Choice of effective messaging protocols for iot systems: Mqtt, coap, amqp and http, in: 2017 IEEE International Systems Engineering Symposium (ISSE), 2017, pp. 1–7, doi:10.1109/SysEng.2017.8088251. [15] D. Dragan, D. Tudose, D. Dragomir, Enablement of coap stack on sparrow wireless sensor network, in: 2017 21st International Conference on Control Systems and Computer Science (CSCS), 2017, pp. 625–629, doi:10.1109/CSCS.2017.95. [16] M. Iglesias-Urkia, A. Orive, M. Barcelo, A. Moran, J. Bilbao, A. Urbieta, Towards a lightweight protocol for industry 4.0: an implementation based benchmark, in: 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), 2017, pp. 1–6, doi:10.1109/ECMSM.2017.7945894. [17] O. Hongzhi, W. Xinlin, Z. Weihua, L. Yuehua, Design of auto-guard system based on rfid and network, in: 2011 International Conference on Electric Information and Control Engineering, 2011, pp. 1292–1295, doi:10.1109/ICEICE. 2011.5777475. [18] A. Imteaj, T. Rahman, M.K. Hossain, M.S. Alam, S.A. Rahat, An IoT based fire alarming and authentication system for workhouse using raspberry pi 3, in: 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017, pp. 899–904, doi:10.1109/ECACE.2017.7913031.
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Ad Hoc Networks journal homepage: www.elsevier.com/locate/adhoc
An IoT-based smart cities infrastructure architecture applied to a waste management scenario Patric Marques, Diogo Manfroi, Eduardo Deitos, Jonatan Cegoni, Rodrigo Castilhos, Juergen Rochol, Edison Pignaton, Rafael Kunst∗ Informatics Institute Federal University of Rio Grande do Sul Av. Bento Goncalves, 9500 - Porto Alegre, RS - Brazil
a r t i c l e
i n f o
Article history: Received 6 March 2018 Revised 11 October 2018 Accepted 16 December 2018 Available online 28 December 2018 Keywords: Internet of things Smart cities Energy efficiency Intelligent waste management Wireless communications
a b s t r a c t Studies estimate that by 2050 two thirds of the world population will be leaving in urban areas, what leads to the necessity of intelligent services to meet the needs of the cities residents. An emerging solution to deal with this scenario is the convergence of information and communication technologies through the implementation of the concepts of smart cities and Internet of Things to provide solutions in diverse fields like infrastructure, transportation, and surveillance. Considering this challenging scenario, in this article a multilevel IoT-based smart cities infrastructure management architecture is proposed and the waste management problem is used as a case study to evaluate the performance of the proposed solution. Results proved the concept of the architecture, showing that it is able to manage up to 3902 garbage bins simultaneously. These bins are able to correctly separate organic and recyclable waste in both indoor and outdoor scenarios, presenting low response times, what leads to a good quality of experience to the users of the system. © 2018 Elsevier B.V. All rights reserved.
1. Introduction The United Nations estimate that by 2050 almost two thirds of the world’s population will be living in urban areas, increasing the already high population density of big cities [1]. With the increase of the urban population, the development of infrastructure and services will become indispensable to meet the needs of the cities residents [2]. An emerging solution to deal with this scenario is the convergence of information and communication technologies through the implementation of the concept of smart cities. This concept is based on the idea of using Internet of Things (IoT) sensors and devices to intelligently implement solutions that meet the demands generated by this expected scenario [3]. These future urban areas will demand solutions in diverse fields, including city services infrastructure, transportation, surveillance, and technology related issues. The efficient management of these kinds of services has a significant impact on the quality of life of the citizens [4]. Considering this challenging scenario, the implementation of the IoT concepts becomes mandatory for smart cities, since it allows objects to connect with each other and interact with humans
∗
Corresponding author. E-mail addresses: [email protected] (P. Marques), [email protected] (E. Deitos), [email protected] (J. Cegoni), [email protected] (R. Castilhos), [email protected] (J. Rochol), [email protected] (E. Pignaton), [email protected] (R. Kunst). https://doi.org/10.1016/j.adhoc.2018.12.009 1570-8705/© 2018 Elsevier B.V. All rights reserved.
in a pervasive and intelligent way [5]. One of the services which is becoming important in this context is the efficient management of the waste generated in big cities. Several works propose efficient solutions for intelligent garbage collection using the concepts of IoT. Shyam et al. [6] developed an IoT-based system that measures the level of waste in residential waste bins and sends this data to a server, aiming at improving garbage collecting routes in big cities. The system proposed by Bharadwaj et al. [7] implements LoRa communication technology to notify the collection systems when waste bins are full. Hong et al. [8] presented a successful IoTbased system for waste control which is currently implemented in South Korea. The main concept behind the proposal is that at the time of disposal, residents are identified by RFID cards in waste bins. The waste is weighed and the information is sent to a server that automatically processes this information for billing purpose. Although very relevant, the proposals currently found in the literature are mainly focused on garbage collection, not taking into account another important aspect, which is the correct waste separation considering the characteristics of the disposed products. Taking into account this unsolved problem, in this article a multilevel IoT-based smart cities infrastructure management architecture is proposed and the waste management is used as a case study to evaluate the performance of the proposed solution. The multilevel approach allows the integration of physical objects, communication infrastructure, cloud platform, and IoT-based services in a perva-
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sive way, what facilitates the implementation of diverse kinds of services in the context of smart cities. The main goals and contributions of the proposed solution are presented as follows. • Modular design, allowing independent and simultaneous execution of the different layers of the architecture to provide support to multiple protocols and services; • To easily integrate devices and cloud services under different communication network protocols; • Low power consuming solution, allowing the IoT devices battery to last longer; • Communications network quality of service (QoS) metrics are taken into account to guarantee that the response times are acceptable; • Evaluation of the performance of the proposed solution considering different communication protocols in real world waste separation scenarios. The proposed architecture is implemented using a Raspberry Pi hardware and is evaluated considering a case study of intelligent waste management. This case study considers two real world scenarios: (I) an indoor implementation to evaluate the behavior of the solution in a typical house, and (II) an outdoor scenario, where garbage bins equipped with the proposed solution are available in a big city park. In both situations, the proposed architecture is able to correctly separate the waste accordingly to the characteristics of the disposed products. Another concern of the proposed solution is to guarantee the confidentiality of the system users, therefore, three different protocols are evaluated to implement secure network communications: Message Queuing Telemetry Transport Protocol (MQTT), Constrained Application Protocol (CoAP), and Secure Hypertext Transport Protocol (HTTPS). The performance of each protocol is evaluated considering both power consumption and QoS-related metrics in order to identify the best one for implementation in indoor and outdoor scenarios. The remainder of this article is organized as follows. In Section 2, background aspects on IoT-based waste management are provided considering the related works currently found on the specialized literature. The proposed architecture is presented and discussed in Section 3. The evaluation methodology and the results obtained from the real world implementation of the proposed solution are presented in Section 4. Conclusions and directions for future investigations are provided in Section 5. 2. Background on IoT-based waste management Among several IoT-based services provided in smart cities, one of primary importance is the waste management. Dealing with this kind of service is becoming challenging due to the fast growing pace of the metropolitan areas of big cities. An emerging approach to provide efficient waste management in this scenario is to use Radio Frequency Identification (RFID) technology to help classifying the kinds of disposed products. This classification relies also on creating and maintaining databases to store characteristics of a large amount of products. Therefore, storage and processing of the information related with these products is often conducted in cloud environments, what creates another challenge related to providing QoS-enabled communication with the cloud. Considering the growth in the urban population and the consequent increasing demands for intelligent services as waste management, many IoT-based solutions have been presented in related works. Shyam et al. [6] reports the development and simulation of an intelligent mechanism to improve waste management in big cities. The proposed system is based on a geographic information system, which is combined with optimization algorithms. Comparisons are performed to evaluate the efficiency of a traditional
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static collection model compared to the proposed dynamic IoTbased garbage collection. Despite proposing a relevant solution, no details regarding the network infrastructure and its performance are provided. Bharadwaj et al. [7] propose a system that identifies the status of the waste bins. The system is able to calculate routes aiming at optimizing the resources used for garbage collection in cities. The proposed solution relies on LoRa Wireless Sensor Networks standard for communication purpose. The solution proposed by the authors makes use of the Google direction Application Programming Interface (API) to calculate routes. The main shortcoming of this related work, compared with the solution proposed in this article is that problems related to the separation of the products to be disposed are not considered in the presented solution. Hong et al. [8] present a solution in which RFID readers are installed in the waste bins to identify the individuals who are discarding waste in each bin. The system uses the collected information along with the weight of the discarded bin to feed a billing system. The waste bins are distributed at various locations within the city and are inter-connected using a mesh wireless network topology. The analysis of the related works provided evidence that despite intelligent IoT-based solutions have been proposed to deal with the waste management study case, there is a lack of evaluations of solutions implemented in the real world. Moreover, communication protocols are studied, but generally without taking into account important aspects like scalability and performance considering QoS metrics. Table 1 summarizes the features covered by related work in comparison with the solution proposed in this article. 3. Proposed architecture The architectural design of the solution proposed in this article brings together the concepts of Cyber Physical Systems (CPS) [9], advanced data communication systems [10], and embedded intelligence [11] to deal with smart cities related challenges. In order to allow the convergence of these concepts, a multilayer approach is defined to allow both independent and simultaneous operation of diverse features of the architecture. Fig. 1 depicts the proposed architecture. The proposed architecture is organized considering the existence of four layers: (I) Physical Objects, (II) Communication, (III) Cloud Platform, and (IV) Services. The first layer aims at making possible to IoT sensors to collect data that will feed the smart city architecture with information used to offer services to the population. After the sensors collect data, a communication device, which can implement different technologies, such as RFID, Bluetooth, and Zigbee, is used collect sensors data. This data is processed by a NodeMCU, which communicates with a local processing unit, responsible for gathering information used by the application which is providing a service. The local processing implemented in the Physical Objects layer brings elements of edge computing [12], as it pushes part of the computation to edge nodes, instead of relying in concentrating all the computation in a centralized remote server, for instance. Compared to similar architectures described in [12], the architecture here proposed provides additional security features for this type of network part, usually composed of resource constrained nodes, which are not explored in the [12]. Another comparable approach that provides a case study applying an edge computing algorithm integrated to an IoT mesh network in the context of a smart building system integrated is presented in [13]. Despite the similar idea of pushing part of the computation to the edge, the authors in [13] are not concerned neither with security, nor with performance aspects, as explored in this proposal. Some applications demand
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Ad Hoc Network LoRa Wireless Mesh Network CoAP, HTTPS, and MQTT
Theoretical
Protocols Analysis
RFID
Realistic Scenario
Scenarios
QoS
Power
X
X X X X
Outdoor Outdoor Outdoor Indoor and outdoor
X
X
X X
X X
Fig. 1. Architecture Design.
high computation power and/or the storage of large amounts of data. To provide the infrastructure for these specific applications, the proposed architecture facilitates access to a cloud platform that is responsible for providing compute engine and data storage services. IoT sensors are physical objects designed to execute different kinds of tasks and consequently collect various types of data. This characteristic of the IoT devices usually leads to variable amounts of data that need to be transmitted using different network technologies. The network technology to be used is defined considering both the amount of data to be transmitted and the physical implementation of the IoT device. Therefore, from the point of view of providing the infrastructure necessary to accommodate the sensors used to provide services in the context of smart cities, a variety of network technologies must be supported by the proposed architecture. To deal with different network access technologies, the proposed solution defines a communication layer that supports the implementation of various wireless technologies. The definition of the technology to be used is a responsibility of the local processing unit, which is located in the Physical Objects Layer and relays data to the communication layer using the interface of a network access point. This layer provides communications among all layers of the architecture.
The third layer of the proposed solution is the Cloud Platform, designed to provide three kids of services: processing, database queries, and data storage. Each of these services can be allocated dynamically to meet the requirements of different kinds of applications in the context of smart cities service provisioning. Although cloud solutions are very common nowadays, it is important to emphasize that not every type of applications and services require a cloud platform to operate properly. Considering this scenario and also that one of the design goals of the proposed architecture is to be generic enough to support any kind of service, this layer is always offered as part of the infrastructure provided by the proposed solution, however, its implementation is optional. In situation in which the cloud platform is not required, the local processing unit, located in the physical objects layer becomes responsible for data processing, storage and database operations. Another important feature of the architecture is the flow of information. Special attention is given to the fact that in the implementation of smart cities related services, a considerable amount of personal information is generally necessary for the applications to work properly. Due to the sensitivity of this kind of information, implementing solutions to guarantee the confidentiality of the transmitted data is of paramount importance. To deal with the confidentiality related challenges, the proposed solution supports
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different secure protocols that apply the concepts of cryptography to provide secure communications even when the transmissions pass through insecure channels, what is the case of commercial wireless networks. Examples of protocols supported by the proposed architecture are MQTT, CoAP, and HTTPS [14]. Aside from the secure communications protocols, a flow of information and interfaces are defined to allow data exchange among the different levels of the architecture. Specifically, in the physical objects layer, a flow of sensors data is defined to feed the local processing unit with information. Moreover, the cloud platform and the service layer have application and control data flows, respectively. Smart city related applications, in the proposed architecture, are located in the services layer. This layer implements four groups which are called classes of services: (I) Surveillance, (II) Transportation and Logistics, (III) Infrastructure, and (IV) Technology. In each class, different kinds of applications can be implemented to deal with the challenges of smart cities. It is important to emphasize that the proposed architecture is a generic solution, so the underlying layers are designed to offer support to the applications and therefore can be adapted to the specific implementation of a given service. Considering this characteristic of the proposed architecture, in the next section, a case study of intelligent waste management is presented considering an adaptation of the generic architecture applied to deal with a real world problem. 4. Case study and performance evaluation In order to evaluate the proposed architecture, this article considers a case study involving an IoT-based waste management system. The adaptations of the architecture to the case study are presented in 4.1. The results are presented and discussed in 4.2. 4.1. Waste management case study This section describes a case study consisting of an IoT-based waste management system that systematically collects information regarding the kinds of products to be disposed in order to identify and indicate the correct destination of each product. In the case study, the proposed architecture is adapted to focus on the specific application of waste management. Fig. 2 presents a specific version of the architecture, already adapted to meet the requirements of the case study. The sensors, in the physical objects layer, are represented, in this case study, by garbage bins equipped with RFID readers, which are designed to collect data from tags located in the products to be disposed off. These tags provide the identification of the product. The data collected by the RFID readers is processed by a Raspberry Pi hardware, which is responsible for coordinating the communication with the databases located in a cloud server, using an IEEE 802.11 device to access the Internet. It is important to highlight that the proposed solution supports other technologies for Internet access, but IEEE 802.11 is flexible enough to operate in both indoor and outdoor scenarios. The implementation of a cloud solution is justified due to the amount of products that need to be registered for the solution to work properly, i.e. to allow the identification of which product is being disposed and indicate the correct garbage bin to be used. Moreover, every disposed product is registered to allow the city administration to create a historical database that can be used to constantly evaluate and improve the garbage collection routes, based on the amount and kind of disposed products. An important concern of the proposed solution is data confidentiality, since the waste disposed by an individual or a family usually contains sensitive personal information. To deal with the confidentiality related issues, in the case study, three secure protocols are evaluated: HTTPS, CoAP, and MQTT. The selection of such
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protocols is based on related works that have conducted theorectical analysis of these protocols ([14], [15], [16]), but were not focused on the evaluation of a real world implementation. Moreover, HTTPS was chosen because it is a well-known protocol, which is widely implemented in Internet-based applications and thus can be easily adapted to the proposed architecture. On the other hand, CoAP and MQTT are recently proposed protocols, designed to deal specifically with IoT-based applications and therefore are considered very relevant in the context of the proposed case study. The implementation of the architecture in a realistic scenario considers the following work flow to guide the users of the system to the correct disposal of products. When a person approaches the garbage bins, RFID readers installed in the bins communicate with a RFID tag located in the container of the product. This information is processed by a Rasberry Pi hardware, which queries the products database (in the cloud platform) to identify the kind of product to be disposed and consequently open the correct bin according to the nature of the product to be disposed (organic or the type of recycle garbage). After the disposal, information about the product, such as its name, type, and weight are uploaded to the historical database, located in the cloud, along with the location of the garbage bin. It is important to note that a proximity sensor installed next to the garbage bins activates the system only when it is necessary, aiming at reducing power consumption. The evaluation of the proposed architecture considers two scenarios. The first one represents the management of waste inside residences in an indoor environment. The second one considers an outdoor environment, in which garbage bins equipped with the system are installed in a public park located in a big city. The residential scenario is presented in Fig. 3 (a). In this case, two garbage bins are available, one for organic waste and another for recyclable product containers. The experiments performed in this scenario consider the usage of the bins in three periods during a day, morning, midday, and evening to represent the profile of the residents of a typical home, i.e. waste generated during breakfast, lunch, and dinner. The second scenario is designed to evaluate the performance of the system in a public area, as depicted in Fig. 3 (b). This scenario considers four different types of garbage bins, one for organic waste and three for different kinds of recyclable waste, i.e. paper, glass, and plastic. In this scenario, the expected number of message exchanges is larger than in the residential scenario. This behavior is expected because in this scenario the waste disposal depends on the amount of people in that given public place along the day. For the sake of the experiment, it is considered that a waste disposal occurs every 15 minutes, following a random selection of products. In technical terms, the deployment of the solution considers that each garbage bin is equipped with a MF RC522 RFID reader manufactured by NXP. This is a low power consuming hardware that supports both read and write operations, communicating at 13.56MHz frequency. The specification of this RFID reader considers ISO 14443A standard and provides three connection interfaces: SPI, I2C, and serial UART [17]. In the proposed solution, the reader is connected to a ESP-12F NodeMCU module, which is a Wi-Fi Development Kit manufactured by Espressif Systems. This kit was selected because it is a low cost open source WiFi module typically used for the implementation of IoT-based applications. The local processing unit is implemented using a Raspberry Pi 3 Model B platform. The Raspberry Pi is a low cost, low power demanding, single board computer, which can handle multiple functions. It is equipped with a 1.2Ghz 64-bit quad-core processor. This Raspberry Pi board has a built in module which implements IEEE 802.11n standard [18], which was used for WiFi based Internet access, implemented in the proposed solution to communicate with the cloud platform. Table 2 summarizes the main characteristics of the scenarios considered for performance evaluation.
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Fig. 2. Case Study Architecture.
Fig. 3. Study Case Scenarios.
4.2. Results and discussion In this subsection the results obtained from the real world implementation of the proposed IoT-based waste management case study are presented and discussed. The basic configuration of the
experiments consider 100 waste disposal in each garbage bin for each evaluated scenario and protocol configuration. It is also important to emphasize that for the residential scenario, the disposals occur at a lower rate compared to the public park scenario, due to the modeled used behavior, which is concentrated in three
P. Marques, D. Manfroi and E. Deitos et al. / Ad Hoc Networks 87 (2019) 200–208 Table 2 Scenarios deployment characteristics.
Environment Recycle Garbage Bins Organic Garbage Bins Communication technology Network Layer Local processing unit CoAP implementation HTTPS implementation MQTT implementation
Scenario 1: Residence
Scenario 2: Public Park
Indoor 1 1 RFID WiFi Raspberry PI Microcoap server OpenSSL and Apache Mosquitto Broker
Outdoor 3 1
Table 3 Electric current consumed by NodeMCU and RFID reader. Device
Mode
Electric Current (mA)
NodeMCU - IEEE 802.11 NodeMCU - IEEE 802.11 MFRC 522 - RFID reader MFRC 522 - RFID reader
Operation Sleep Operation Sleep
74.523 4.851 16.012 1.413
specific periods of the day. Three main approaches are considered to evaluate the proposed architecture considering the waste management case study. First, results related to the power consumption are presented. The second kind of results are related to the QoS guaranteed in network transmissions. In this sense, latency, jitter, and throughput metrics are evaluated. Finally, the amount of garbage bins supported by each kind of protocol is studied taking into account the implementation of HTTPS, MQTT, and CoAP. Consuming low amounts of power is of paramount importance in an IoT-based scenario to increase the battery life of the sensors. In this specific case study, the goal is to evaluate the energy consumed by the devices in situations where HTTPS, MQTT, and CoAP protocols are implemented. It is important to note that the electric current consumed by the NodeMCU is measured separately from the current demanded by the RFID reader. This approach guarantees that the energy consumption considered for evaluation purposes only depends on the performance of the protocol and is not dependent on the random behavior of RFID cards reading. Both the NodeMCU and the RFID reader have two modes of operation: sleep mode and operation mode (or non-sleep). Regardless of which protocol is implemented in the NodeMCU, the measured values of electric current do not change while the devices are in sleep mode. These values, however are changed when the device is configured to be used in the operation mode. The average electric current consumed in each configuration is shown in Table 3. The first analysis of this case study is based on Fig. 4, which plots the behavior of the electric current considering the implementation of CoAP, MQTT, and HTTPS in both operation and sleep modes. The presented data was acquired in one of the garbage bins in the outdoor scenario and represent the average energy consumption considering the implementation of different secure transmission protocols. The overall experiment took around 12 seconds, considering that each protocol was executed for about 4 seconds. Initially, each protocol is configured to start in sleep mode. The activation of the operation mode can be clearly observed in the graph presented in Fig. 4 by analyzing the peaks, which can be observed between the seconds 3 and 4 (HTTPS); 5 and 6 (CoAP); and 7 and 8 (MQTT). The reason for such occurrence is correlated to the existence of a led connected to the Reset pin of the NodeMCU, which is activated when the protocol state changes from sleep to operation mode. As can be seen in the figure, all protocols present similar behaviors in terms of electric current when the operational status of the architectural components is altered.
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Another analysis related to power consumption is conducted to correlate the amount of waste disposals with the power consumed by the proposed solution. This kind of evaluation is important to allow the assessment of the devices battery life. Considering the experimental parameters presented in Table 3, it is possible to calculate the power consumption of the devices in each operation mode. In the specific case study, the cost-benefit of enabling or not sleep mode is evaluated and the results are presented in Fig. 5. To evaluate the cost-benefit, the power consumption (E) is calculated following Eq. (1), where V represents the voltage supply of the NodeMCU, which is set to 5V. I is the electric current demanded by the IEEE 802.11 and t is the duration of the communication, which is set to 2129 ms in this experiment.
E = V × I × t
(1)
Considering the evaluated scenario, the implementation of sleep mode proves to be advantageous since it consumes less energy in all practical situations. Not implementing sleep mode would become an advantage only in situations where more than 90 discards are made in a period of 2129 ms, what corresponds to a disposal every 25 ms, configuring an unrealistic scenario. The second approach to evaluate the proposed architecture is related to QoS metrics. The first metric analyzed is the round-trip latency, considering the communication between the garbage bins located in both indoor and outdoor scenarios with the cloud platform. The QoS-related experiments were performed to evaluate the time demanded by the system to correctly identify the garbage bin to be opened considering the type of waste to be disposed. Guaranteeing a low latency is very important for this kind of implementation, since the users should not wait long times for a bin to open. The outcomes of the latency related experiments in the indoor scenario are presented in Fig. 6 (a), while the results regarding the outdoor scenario are shown in Fig. 6 (b). In both scenarios, the results reflect the average latency measured during the experiments. The first impression when analyzing the graph shows that all protocols provide relatively low latency, keeping the response times below 12ms in the indoor scenario and lower than 14ms in the outdoor scenario. Besides guaranteeing low response times, it is important to emphasize that in all experiments the correct bin was selected by the system. In most situations not implementing sleep mode provides faster responses, what is explained by the time demanded to restart the modules when sleep mode is implemented. However even in sleep mode, the latency is acceptable for real world implementations of the architecture. Therefore, considering the performance of each protocol and taking into account that the sleep mode consumes less power, it is possible to conclude that the best cost-benefit considering the latency metric in both indoor and outdoor scenarios is to implement MQTT with the sleep mode enabled. The average Jitter is the second QoS-related metric evaluated in this case study. This metric is calculated considering the variations on the latency of the communication when a disposal occurs. Analyzing Jitter is important for the analyzed scenarios because a low value guarantees that the response times are consistent in every disposal, what leads to quality of experience for the users of the waste management system. Results related to the Jitter values measured in the indoor scenario are presented in Fig. 7(a) and the outcomes of the experiments for the outdoor scenario are depicted in Fig. 7(b). Analyzing the results it is possible to observe that, in general, Jitter is higher in outdoor measurements, what is expected, since this is a less controlled scenario. Another noticeable behavior is that there is no significant variability in the Jitter when the operation mode (sleep or non-sleep) is changed. Therefore, considering the power consumption, the operation mode, and the different
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kinds of secure transmission protocols, MQTT configured to operate in sleep mode, is the one which provides the best cost-benefit according to this experiment. Network throughput is another QoS metric that affects the users quality of experience, since it impacts on the time required for a garbage bin to open for a given user to dispose the waste. In this case study, the throughput is measured using Wireshark to calculate the amount of data exchanged between the garbage bins and the cloud platform. The amount of bins is varied between 1 and 4 to reflect both indoor and outdoor scenarios. Moreover, the system is stressed to evaluate the maximum throughput that can
be attained after the implementation of CoAP, HTTPS, and MQTT protocols. The outcomes of these experiments are summarized in Table 4. The analysis of the results show that in the evaluated scenarios, HTTPS attains the highest throughput. Although this result is relevant, it was obtained in a limited scenario, designed to prove the concept of the proposed architecture. Therefore, to scale the solution to a more realistic scenario, it is also important to evaluate the maximum throughput of each protocol, obtained after stressing the system. In such situation, it is possible to conclude that MQTT protocol surpasses HTTPS, becoming the protocol that pro-
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Table 4 Throughput Analysis.
Table 5 Amount of Supported Garbage Bins.
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Table 6 Cost-benefit Analysis Summary.
vides the best throughput considering a typical implementation of the solution in a big city. For the final analysis conducted in this article, the throughput data is extrapolated to obtain the expected amount of garbage bins supported by each analyzed protocol. In order to do that, a linear regression technique using the least squares method is applied to obtain the equation that describes the behavior of each protocol. This type of extrapolation is feasible as there is no factor that would change the deployed setup, besides the number of nodes. Following this rationale, the number of garbage bins distributed in a big city needed to bring the system to its limits for each protocol is calculated and presented Table 5. After analyzing all metrics, it is important to come to a conclusion regarding which protocol fits better to the scenarios evaluated in this case study. In order to do that, in Table 6, the protocol
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which presents the best cost-benefit for each evaluated metric or operation mode is presented. As can be seen, in most situations, MQTT is highlighted as the best solution, however, CoAP has similar performance with the advantage of being more scalable and therefore, one can conclude that it is the protocol which provides the best results for the analyzed scenarios.
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5. Conclusion and future work This article proposed a multilevel architecture to support IoTbased smart cities systems. The goal of this proposal was to address the increasing demand for intelligent services in the continuous growing urban environments. As a case study, the article presented a waste management system to evaluate how the general architecture adapts to particular implementation that aim at solving specific smart cities related challenges. This case study was selected because waste management is an important problem in big cities and also provides the opportunity to explore at least two evaluation scenarios, one indoor and another outdoor. Based on these waste management scenarios, the architecture was implemented along with three different protocols designed to provide secure communication, namely CoAP, HTTPS, and MQTT. The resulting system was evaluated taking into account energy consumption, latency, Jitter, and throughput as evaluation metrics. Based on the acquired results, the scalability was also analyzed considering the impact of a growing number of concurrent garbage bins in the system. Results showed that CoAP is the protocol which supports the higher amount of concurrent users, guaranteeing the coexistence of up to 3902 garbage bins. In terms of power consumption, it was proved that sleep mode is recommended despite of the secure communication protocol which is being implemented. Finally, latency, Jitter, and throughput QoS related metrics were also evaluated. In this specific evaluation, MQTT obtained the best results, however CoAP also performed very well. Considering all the results obtained in a real world experiment, it is possible to conclude that CoAP provides the best cost-benefits, since it supports a higher amount of garbage bins while provides an acceptable level of QoS. This article proved a concept by implementing an architecture which allowed intelligent waste management in the context of smart cities. Although relevant results were obtained, there is still space for future investigations. In this sense, an interesting approach is to implement other protocols designed to operate in the context of IoT systems, such as AMQP and XMPP. Another important analysis would be to consider the implementation of other network layer technologies, like 5G, LTE-Advanced, IEEE 802.22, and Licensed Shared Access to improve even more the QoS offered to the system users. Finally, a very important future work includes the implementation of the solution in a larger scale, involving, for example celebrating an agreement with a city administration focusing on increasing the amount of public spaces where the system is implemented. References [1] World Urbanization Prospects. 2014 Revision, Technical Report, 2014. United Nations, Department of Economic and Social Affairs http://www.un.org/en/ development/desa/publications/2014-revision- world- urbanization- prospects. html.
[2] H. Arasteh, V. Hosseinnezhad, V. Loia, A. Tommasetti, O. Troisi, M. Shafiekhah, P. Siano, Iot-based smart cities: a survey, in: 2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC), 2016, pp. 1–6, doi:10.1109/EEEIC.2016.7555867. [3] T. hoon Kim, C. Ramos, S. Mohammed, Smart city and iot, Future Gener. Comput. Syst. 76 (2017) 159–162, doi:10.1016/j.future.2017.03.034. [4] T. Anagnostopoulos, A. Zaslavsky, K. Kolomvatsos, A. Medvedev, P. Amirian, J. Morley, S. Hadjieftymiades, Challenges and opportunities of waste management in iot-enabled smart cities: a survey, IEEE Trans. Sustainable Comput. 2 (3) (2017) 275–289, doi:10.1109/TSUSC.2017.2691049. [5] R. Kunst, L. Avila, E. Pignaton, S. Bampi, J. Rochol, Improving network resources allocation in smart cities video surveillance, Comput. Netw. 134 (2018) 228– 244, doi:10.1016/j.comnet.2018.01.042. [6] G.K. Shyam, S.S. Manvi, P. Bharti, Smart waste management using internet-ofthings (iot), in: 2017 2nd International Conference on Computing and Communications Technologies (ICCCT), 2017, pp. 199–203, doi:10.1109/ICCCT2.2017. 7972276. [7] A.S. Bharadwaj, R. Rego, A. Chowdhury, Iot based solid waste management system: a conceptual approach with an architectural solution as a smart city application, in: 2016 IEEE Annual India Conference (INDICON), 2016, pp. 1–6, doi:10.1109/INDICON.2016.7839147. [8] I. Hong, S. Park, B. Lee, J. Lee, D. Jeong, S. Park, IoT-based smart garbage system for efficient food waste management, Sci. World J. 2014 (2014), doi:10.1155/ 2014/646953. [9] J. Lee, B. Bagheri, H.-A. Kao, A cyber-physical systems architecture for industry 4.0-based manufacturing systems, Manuf. Lett. 3 (Supplement C) (2015) 18–23, doi:10.1016/j.mfglet.2014.12.001. [10] M. Wollschlaeger, T. Sauter, J. Jasperneite, The future of industrial communication: automation networks in the era of the internet of things and industry 4.0, IEEE Ind. Electron. Mag. 11 (1) (2017) 17–27, doi:10.1109/MIE.2017.2649104. [11] J. Wang, Y. Sun, W. Zhang, I. Thomas, S. Duan, Y. Shi, Large-scale online multitask learning and decision making for flexible manufacturing, IEEE Trans. Ind. Inf. 12 (6) (2016) 2139–2147, doi:10.1109/TII.2016.2549919. [12] M. Satyanarayanan, The emergence of edge computing, Computer (Long Beach Calif) 50 (1) (2017) 30–39, doi:10.1109/MC.2017.9. [13] A. Gajjar, Y. Zhang, X. Yang, A smart building system integrated with an edge computing algorithm and iot mesh networks: Demo abstract, in: Proceedings of the Second ACM/IEEE Symposium on Edge Computing, in: SEC ’17, ACM, New York, NY, USA, 2017, pp. 35:1–35:2, doi:10.1145/3132211.3132462. [14] N. Naik, Choice of effective messaging protocols for iot systems: Mqtt, coap, amqp and http, in: 2017 IEEE International Systems Engineering Symposium (ISSE), 2017, pp. 1–7, doi:10.1109/SysEng.2017.8088251. [15] D. Dragan, D. Tudose, D. Dragomir, Enablement of coap stack on sparrow wireless sensor network, in: 2017 21st International Conference on Control Systems and Computer Science (CSCS), 2017, pp. 625–629, doi:10.1109/CSCS.2017.95. [16] M. Iglesias-Urkia, A. Orive, M. Barcelo, A. Moran, J. Bilbao, A. Urbieta, Towards a lightweight protocol for industry 4.0: an implementation based benchmark, in: 2017 IEEE International Workshop of Electronics, Control, Measurement, Signals and their Application to Mechatronics (ECMSM), 2017, pp. 1–6, doi:10.1109/ECMSM.2017.7945894. [17] O. Hongzhi, W. Xinlin, Z. Weihua, L. Yuehua, Design of auto-guard system based on rfid and network, in: 2011 International Conference on Electric Information and Control Engineering, 2011, pp. 1292–1295, doi:10.1109/ICEICE. 2011.5777475. [18] A. Imteaj, T. Rahman, M.K. Hossain, M.S. Alam, S.A. Rahat, An IoT based fire alarming and authentication system for workhouse using raspberry pi 3, in: 2017 International Conference on Electrical, Computer and Communication Engineering (ECCE), 2017, pp. 899–904, doi:10.1109/ECACE.2017.7913031.