MDSDV: a modified DSDV routing mechanism for wireless mesh networks

The Journal of China Universities of Posts and Telecommunications December 2011, 18 (Suppl. 2): 34–39 www.sciencedirect.com/science/journal/10058885

http://jcupt.xsw.bupt.cn

MDSDV: a modified DSDV routing mechanism for wireless mesh networks WANG Kai1 ( ), GAO Yang-yang1, GUAN Jian-feng2, QIN Ya-juan1 1. National Engineering Laboratory for Next Generation Internet Interconnection Devices, Beijing Jiaotong University, Beijing 100044, China 2. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China

Abstract Wireless mesh networks (WMNs), which are consisted of mesh routers and mesh clients, have emerged as a key technology for next-generation wireless networking. WMNs integrate the advantages of wireless local area networks (WLAN) and ad hoc networks and more and more researches have focused on it. In WMNs, routing mechanisms can significantly affect WMNs’ performance and optimal routing mechanisms are imperative to gain the potential advantages of WMNs. In research of WMNs’ routing mechanisms, previous work mostly focuses on modifying the existing ad hoc routing mechanisms while this paper focuses on modifying destination-sequenced distance-vector routing mechanism (DSDV) with cross-layer design method and proposes the modified destination-sequenced distance-vector routing mechanism (MDSDV) for WMNs. Different from DSDV, the proposed MDSDV uses the integrated effects of bandwidth and hop count as the routing metric for selecting appropriate routes. Moreover, this paper simulates the proposed MDSDV in the network simulator-2 (NS2) comparing with previous DSDV and the ad hoc on-demand distance vector (AODV) routing. The simulation results show that the proposed MDSDV can preferably fit the specific characteristics of WMNs and it is the relative best choice for WMNs which consist of a large number of nodes and need high packet delivery rate, low end-to-end delay and insensitive routing overhead. Keywords DSDV, WMNs, NS2, performance evaluation

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Introduction

WMNs, which can be considered as a mixture of the advantages of the WLAN and the mobile ad hoc network (MANET), have become a key technology used for wireless area network [1]. In WMNs, the nodes automatically establish an ad hoc network and maintain the mesh connectivity. That is, WMNs are dynamically self-organized and self-configured. WMNs are comprised of two types of nodes: mesh routers and mesh clients. Other than the routing capability for gateway/bridge functions as in a conventional wireless router, a mesh router contains additional routing functions to support mesh networking. Through multi-hop communications, the same coverage can be achieved by a mesh router with much lower transmission power. Mesh routers have minimal mobility and form the mesh backbone for mesh clients, whose hardware platforms can be much simpler than those for mesh routers. Received date: 18-11-2011 Corresponding author: WANG Kai, E-mail: [email protected] DOI: 10.1016/S1005-8885(10)60142-2

It is commonly recognized that the routing mechanisms are very significant for all kinds of networks, especially for WMNs because of its specific structure and characteristics. Fortunately, several existing ad hoc routing mechanisms can be directly applied into WMNs due to the similarities between WMNs and MANET. However, this simple migration of the routing mechanisms between the two different networks leads to undesirable downgrade of WMNs performance [2]. There has been much work to improve WMNs’ routing mechanisms with various methods including the modification of routing metrics and introduction of cross-layer design [3]. The typical example of modified routing metrics is the link-state related protocols such as MIT’s SrcRR [4] and the multi-radio link quality source routing protocol (MR-LQSR). The example of cross-layer design is quality of service (QoS) routing protocols, which introduce QoS requirements to routing mechanisms in order to satisfy the specific requirements of some services like multi-media service. In addition to the two methods above, there are still some other methods such as changing from single channel to multiple channels and the design of new network architecture to work

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out the existing dead-end problems, which are caused by the current weak architecture or implementation of new networks primitives attempting to avoid inferior routes. In this paper, we focus on the details of WMNs [1–2] and DSDV routing mechanisms and analyzing their matching points to achieve better network performances. We propose the MDSDV: a modified DSDV routing mechanism for WMNs, which can preferably fit the specific characteristics of WMNs. And then we adopt the NS2 to simulate the performance of the proposed MDSDV and compare it with the AODV routing and the original DSDV. According to the simulation results, we conclude the characteristics of the MDSDV. And both the advantages and disadvantages of MDSDV compared with that of AODV and the original DSDV are presented in this paper. In the end, as for the problems still exist, we propose the direction of our future work. The rest of this paper is organized as following. Sect. 2 introduces the background of WMNs, cross layer design and DSDV routing mechanisms, and analyzes the integration of DSDV and WMNs. In Sect. 3, we propose the MDSDV, which is a modified DSDV routing mechanism for WMNs. Sect. 4 simulates the MDSDV in NS2 and evaluates its performance compared with that of DSDV and AODV. Finally, we conclude this paper and present our future research in Sect. 5.

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Background and motivation

In this section, we introduce the WMNs, cross layer design and DSDV in detail. Moreover, we analyze the integration of DSDV and WMNs. 2.1 WMNs WMNs are consisted of two categories of nodes including mesh routers and mesh clients. Mesh routers contain additional routing functions to support mesh networking, which make up wireless backhaul networks with relative stationary topology for wireless clients. Mesh clients have much simpler hardware platforms but better mobility than mesh routers. WMNs have such characteristics as follows: 1) Self-organized and self-configured: the nodes can automatically establish an ad hoc network and maintain the mesh connectivity; 2) Two types of mesh nodes: mesh clients and mesh routers; 3) Multi-hop wireless networks connected by the mesh routers; 4) Different power consumption constraints for mesh routers and mesh clients; 5) Compatible with other kinds of wireless networks and the ability of interconnecting various kinds of networks. Due to the above referred characteristics, WMNs attract

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lots of attention among worldwide researches. Given the characteristics of WMNs, we can conclude the similarities and differences between WMNs and MANET in Table 1. Table 1 Comparison of WMNs and MANET Comparison

WMNs

MANET

Mobility

Mesh routers as the main network part, minimal mobility; no constraints of power consumption.

User nodes as the main network part, high mobility; constraints of power consumption.

Network scalability

Large number of nodes; interconnection of various kinds of wireless networks.

Small number of nodes, usually several decade nodes; only one kind of wireless network.

Service type

Providing access for client nodes; wireless sub-network access to network.

Providing node to multi-node transmission; providing the function of user access.

One key challenge to achieve the potential advantages of WMNs is to design and implement optimal routing mechanisms. As for the optimal routing mechanisms, there are several standards as follows [1–2]: 1) Multiple routing metrics: the ability to choose more appropriate routes based on network requirements; 2) Scalability: the ability to satisfy the requirements of WMNs interconnection; 3) Robustness: the ability to handle link failures and network congestions; 4) Efficiency: making the routing mechanisms efficient for mesh backhaul network; 5) Minimal mobility and no power consumption constraints. Several existing routing mechanisms have considered one or two of the requirements above. For example, some routing mechanisms have various performance metrics [5], and some others are multi-radio routing [6] and multi-path [7] routing mechanisms or geographic routing mechanisms [8]. However, they are far beyond the potential optimization performance. To improve routing mechanisms, several methods have been developed to design new routing mechanisms. In this paper, we focus on the cross-layer design routing mechanisms for WMNs, which can make the best use of the network resources based on integrating the related information. 2.2

Cross layer design

The cross layer design can use the integrated network resources to maximize the efficiency while satisfy the network requirements and limitations. One typical cross layer design example is QoS routing, which applies QoS requirements into routing mechanisms and can better satisfy services QoS requirements. In this paper, we focus on modifying DSDV with the cross layer design method, which is promising for satisfying the requirements of WMNs.

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2.3

DSDV routing mechanism

DSDV is a table-driven routing mechanism and is a typical proactive routing mechanism based on Bellman-Ford algorithm [9]. In DSDV, there are two types of updating routing tables which are time-driven update and event-driven update. For DSDV routing mechanism, each node maintains a routing table and periodically broadcasts update messages to adapt to the mobile network topology, which is called time-driven update. In other cases, if the trigger of the routing update is based on the network topology, it is called event-driven update. In DSDV, the employment of destination sequence number can avoid time-out routes, which can avoid the invalid routes. Each destination node creates and records an individual destination sequence number. When a node receives another route entry to the same destination, it will substitute the route entry with the newer received one only if the sequence number is newer than the previous one. If the sequence number is the same as the previous one, it depends on the parameter of hop count to choose the less hop count route. If both the sequence number and the hop count are equivalent, the table entry would remain the same without any change. The characteristics of DSDV are shown as follows: 1) Low delay to obtain routes which is appropriate for real-time services. Low delay is owing to that DSDV routing mechanism could choose an invalid route after the previous route fails. 2) The destination sequence number can not only identify the sequences of route entries, but also avoid route loops. 3) Each node maintains a routing table, which records the destination address, hop count to the destination and a sequence number received from the destination node. 4) Two kinds of updating routing tables: time-driven and event-driven. The time-driven update means periodically broadcasting messages to update routing tables, which is convenient and easy for new-coming nodes to know the whole network topology and hence preferred in the highly changeable networks. The event-driven update indicates when the network topology changes, this event would trigger the update event, which can quickly correspond to the topology change and hence it’s more applicable for slowly changeable network. From the conclusions above, we can deduce that DSDV has low end-to-end delay, which is suitable for improving the QoS of real-time services. The two kinds of routing updates can make the routing table return to the stable state in a very short period after updates. Therefore, this paper chooses DSDV as the mechanism for mesh routers to achieve better performances. 2.4

Analysis of integrating DSDV and WMNs

The previous work on performances evaluation of ad hoc

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routing [10-14] showed that DSDV is more appropriate for minimal mobility networks and it has low end-to-end delay. Based on the characteristics of WMNs and DSDV described above, there is the potential to integrate DSDV into WMNs to achieve a better performance. After examining the feasibility of applying DSDV into WMNs, we combine the DSDV and the cross-layer design under the consideration of network resources distribution fairness and utility efficiency.

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MDSDV

The previous section introduces the characteristics of WMNs and DSDV, and the results show that they can get the mutual benefits in terms of routing. However, the DSDV still faces many problems including the low throughput and large end-to-end delay when the number of nodes is pretty large. So, this paper proposes a new routing protocol called MDSDV to solve these problems. 3.1

Bandwidth of WMNs

Bandwidth is always the precious resource for most wireless networks. Due to the multi-hop characteristics of WMNs, the bandwidth becomes more important to guarantee the better network performance. To select routes with more bandwidth will definitely optimize the network performance. Thus, we choose the bandwidth distribution fairness and efficiency as the modification purpose of DSDV. In this paper, we introduce the parameter of available bandwidth to assist DSDV to choose routes with a better balance of bandwidth and hop count, which can guarantee the selected routes have better quality. The routes selected under the consideration of available bandwidth are instrumental to avoid congestion and maximize the utility efficiency of bandwidth. Therefore, this policy will further reduce end-to-end delay, and hence offer better performances. 3.2

Details of MDSDV

The modification of DSDV can be described as follows: First, the available bandwidth should be obtained for routes. Secondly, the effects of bandwidth and hop count should be integrated as the routing metric for selecting appropriate routes, would not only reflect the least hop count, but also reflect larger bandwidth to transmit data packets. Thirdly, the available bandwidth should be updated appropriately. 1) Available bandwidth The available bandwidth can be defined as the bandwidth that is not totally taken by others. That is, it can be reserved to

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transmit data packets. Suppose the total bandwidth is s, the bandwidth which has been taken by others is st and the available bandwidth is sa accordingly, then we can deduce, sa s  st (1) That is, the available bandwidth is the total bandwidth minus the bandwidth taken. 2) Model for routing selection When the available bandwidth of a route is obtained, it can be added as an additional entry for the previous existing entry in the routing table. When selecting routes from the routing tables, we will use the hop count and bandwidth which can be used to help make the decision for routing. By integrating the hop count and bandwidth information of routes, we propose a model to make a routing metric for selecting routes. We denote the routing metric of the model as model_metric. Assuming the model_metric is m and the hop count is h, then we can deduce, h m (2) sa s That is, the routing metric model can be described as follows: the model_metric is the hop count divided by the ratio which is the value of the available bandwidth. When making the selection for routing, the routes with less hop count and larger bandwidth are chosen, which have smaller model_metric values. In the MDSDV, the routes with only one hop count but long geographical distance can be avoided, because the effect of the bandwidth and hop count are both considered in Eq. (2). 3) Updating scheme The available bandwidth can never be a constant value, so the updating scheme for this information is important for the MDSDV. We design the updating scheme on the basis of updating scheme of DSDV. When choosing routes for transmitting data packets, the bandwidth updating process which is independent of routing tables updating would be triggered. The route chosen for this event is based on the newest information of bandwidth. Whenever the routing table updates, the bandwidth information will also be updated, through which the information in the routing table can reflect the changes of the network topology and the available bandwidth. The updating process will lead to more overheads when the network topology changes faster. However, the WMNs topology is relatively stationary which does not introduce a large amount of overheads compared with the original DSDV. 3.3

The process of MDSDV

In MDSDV, each node maintains a routing table, which is consisted of the destination address, hop count, destination

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node’s sequence number and the available bandwidth, as shown in Table 2. Table 2 Routing table entry for MDSDV Destination address

Hop count

Sequence number

Available bandwidth

When choosing routes from routing table, the MDSDV employs the routing metric model (Sect. 2) to compute the model_metric and choose the route with the least model_metric value. Once it begins to choose routes from routing table, the process for obtaining available bandwidth will be triggered. When the routing table updating begins, the available bandwidth will update at the same time. As a result, the speed to establish and choose routes can be increased. In the whole process, the MDSDV expands the strengths of the original DSDV in theory. 3.4

Potential values of MDSDV

By introducing available bandwidth into DSDV, it gives us the opportunity to consider bandwidth as well as the hop count when choosing routes for data packets, which improves the quality of selected routes. This modification can also balance the flows among the whole available network bandwidth and thereby avoid some congestions.

4 Performance evaluation In this section, we simulate the performances of MDSDV, original DSDV and AODV with NS2 in different scenarios. Firstly, we modify the DSDV source code to MDSDV in NS-2 platform and then we build the scenarios of simulation for AODV, DSDV and MDSDV. And we establish ad hoc networks with minimal mobility to simulate the wireless backhaul network environment of WMNs. In the scenarios, we set the number of nodes as 10, 20, 30, 50 and 100 respectively in a 1 000h1 000 network topology environment. Then we simulate the performances of AODV, DSDV and MDSDV in the scenarios respectively for 200 times and analyze the average results. Based on the average results of the simulation, we compare the network performances in terms of packet delivery ratio, end-to-end delay and routing overhead as shown in Fig. 1, Fig. 2 and Fig. 3. In which the lines marked by the square, triangle and circle represent AODV, DSDV and the MDSDV, respectively. 4.1

Packet delivery ratio

Packet delivery ratio can be defined as the ratio of successful received packets to all the sent packets. This parameter can

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reflect the network throughput and the efficiency of the network resources usage. Fig. 1 shows the packet delivery ratio of AODV, DSDV and MDSDV in the scenarios with 10, 20, 30, 50 and 100 nodes.

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that of AODV only if the number of the nodes increases to 100. Thus, we can summarize that when the number of nodes increases to be large enough, the MDSDV has lower delay than the original DSDV and AODV. It is definitely the advantages of MDSDV for WMNs which has a large number of nodes. 4.3

Routing overhead

Routing overhead can be defined as the overhead of routing mechanism overhead minus the transmitted data packets. Fig. 3 shows the ratio of the routing overhead to total overhead of AODV, DSDV and the MDSDV in the scenarios with 10, 20, 30, 50 and 100 nodes.

Fig. 1 Simulation results of packet delivery ratio

Fig. 1 shows that the packet delivery ratio of the MDSDV is always higher than that of the original DSDV and AODV. Thus, we can conclude that the packet delivery ratio of MDSDV is the best among the three routing mechanisms. As the node number increases, the performance of the MDSDV is a litter better than that of the original DSDV, which is obviously better than AODV’s performance. Fig. 3

4.2

Simulation results of routing overhead

End-to-end delay

The end-to-end delay can be defined as the average time spent for delivering data packets from one end node to another one. It is an average value reflecting the average speed of transmitting data packets. Fig. 2 shows the end-to-end delay of AODV, DSDV and MDSDV in the scenarios with 10, 20, 30, 50 and 100 nodes.

Fig. 3 shows that the routing overhead of the MDSDV is almost always smaller than that of the original DSDV when the number of nodes is larger than 10, which is always larger than that of AODV. Thus, we can conclude that the routing overhead of the MDSDV is almost the same as the original DSDV, but is larger than AODV. The simulation results from Fig. 1 to Fig. 3 shows that the MDSDV has better performance in terms of the packet delivery ratio and end-to-end delay if the number of nodes is large enough. However, it almost always has worse performance in routing overhead when comparing with the original DSDV and AODV. That is, the MDSDV is suitable for wireless networks which consist of a large number of nodes and need high packet delivery rate, low end-to-end delay and insensitive routing overhead.

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Fig. 2 Simulation results of end-to-end delay

Fig. 2 shows that the end-to-end delay of the MDSDV is always smaller than that of the original DSDV, but smaller than

Conclusions

After the simulations and performance comparisons in the section above, we can conclude that the MDSDV has the higher value in packet delivery ratio, which means that the MDSDV can make better use of the integrate network resources than AODV and the original DSDV. As for the end-to-end delay, the MDSDV has better performance than

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AODV when the number of nodes in WMNs is large enough and always better than the original DSDV. However, the MDSDV has larger routing overhead than AODV, which is relatively the same compared with the original DSDV. For the future work, we will study how to reduce the routing overhead for MDSDV by reconstructing the data structure of messages or employing message compression, and we will analyze the effect of the bandwidth and hop counts on WMN performances, which is more useful in multi-hop and multi-rate networks. Acknowledgements This work was partially supported by the Hi-Tech Research and Development Program of China (2011AA010701), the Fundamental Research Funds for the Central Universities (W11JB00670) (2011RC0507), the National Natural Science Foundation of China (61001122) (61003283) and Beijing Natural Science Foundation of China (4102064).

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