A Graph-based Approach to Compute Multiple Paths in Mobile Ad Hoc Networks

A Graph-based Approach to Compute Multiple Paths in Mobile Ad Hoc Networks Gunyoung Koh, Duyoung Oh 1 and Heekyoung Woo 2 1 School of Electrical Engineering and Computer Science Seoul National University, Seoul, Republic of Korea {kgy, ody}@popeye.snu.ac.kr 2 Division of Information Technology Engineering, Soonchunhyang University, Asan, Republic of Korea {woohk}@sch.ac.kr Abstract. Multipath on-demand routing protocols for mobile ad hoc networks try to reduce control overhead and end-to-end delay by computing multiple paths with a single route discovery process. We propose Graph-based Multipath Routing (GMR), a novel multipath routing protocol that generate the network topology graph to compute all link disjoint paths in the network. The destination node computes link disjoint paths using the local graph search algorithm. We present our simulation results compared with DSR and Multipath DSR 1 Introduction High mobility, limited battery and valuable bandwidth resource of ad hoc networks make the classical routing protocols impractical to be used directly for ad hoc networks. Therefore a number of routing algorithms for ad hoc networks have been proposed. They may be categorized into two distinct groups - proactive protocols including Destination Sequenced Distance Vector (DSDV) [1] and on-demand protocols including Dynamic Source Routing (DSR) [2], Temporally Ordered Routing Algorithm (TORA) [3] and Ad hoc On-demand Distance Vector routing (AODV) [4]. Although some simulation studies [5] have shown that on-demand protocols incur lower routing overheads than proactive protocols, they still have some problems. On-demand routing protocols discover routes via a flooding technique. That is, a message from a source node is delivered to all other nodes. It takes a substantial amount of network bandwidth which is a premium resource in wireless networks. Although there are many research efforts [6] to find efficient flooding methods, reducing the number of flooding initiations is still an important research issue. Multipath routing schemes try to reduce these problems by finding multiple paths through a single route discovery process. The source node chooses a This work was supported by Samsung Electronics and the University IT Research Supporting Program under the Ministry of Information and Communication of Korea

path among multiple paths and starts transferring data packets. If a link on the path broke down, instead of initiating an additional route discovery process, the source node just chooses another path and continues to transfer. New route discovery process (i.e. flooding) is initiated only after all paths have failed. So the number of flooding initiations can be reduced subsequently. Several multipath routing schemes, including Multipath-DSR [7], Split Multipath Routing (SMR) [8], and Ad hoc On-demand Multipath Distance Vector (AOMDV) [9], are recently proposed. It is important that many multipath routing algorithms seek for link disjoint paths among all possible paths. Link disjoint paths guarantee the independence of failures of each path, thus increasing the path availability. But all these link disjoint paths are not required. M. K. Marina and S. R. Das argued that additional routes beyond a few provide only marginal benefit [9]. They selected 3 for the threshold. But we found that previous multipath routing schemes are unable to find existing link disjoint paths in many cases even below 3. We will show some examples and simulation results. In this work, therefore, our goal is to develop a multipath routing scheme that computes sufficient number of link disjoint paths. The reason for reducing the number of flooding initiations is to reduce routing control overhead, so a scheme using more control packets to compute multiple paths is not desirable. So our goal also includes holding down the number of control packets compared with single path routing protocols. To achieve this goal, our scheme, Graph-based Multipath Routing (GMR) uses graph information which represents the abstract network topology. This graph information is constructed by intermediate nodes in a distributed manner and enables the destination to compute link disjoint paths using local graph search algorithms. The rest of this paper is organized as follows. In section 2, previous works related to multipath routing is observed. Proposed GMR protocol is presented in section 3, while simulation results are carried out in section 4. We conclude in section 5. 2 Related Works In this section, we briefly describe the key features of previous multipath routing protocols and also show some examples in which the routing protocols cannot find existing link disjoint paths. Each multipath on-demand protocol is developed on the base of its original single path on-demand protocol, such as DSR and AODV. Multipath-DSR (M-DSR) [7] is a simple multipath extension of the popular DSR. Instead of replying only to the first received RREQ as DSR, the destination node sends an additional RREP for a RREQ which carries a link disjoint route compared with the routes already replied. However, M-DSR can t compute link disjoint paths in many cases because the intermediate nodes drop every duplicate RREQ that may comprise another link disjoint path. Figure 1 illustrates an example that M-DSR doesn t compute link disjoint paths.

Fig. 1. An example that M-DSR doesn t compute link disjoint paths. Node 3 discards one of the RREQs from node 1 and node 2 because it is a duplicate copy. Split Multipath Routing (SMR) [8] is another multipath variant of DSR. SMR introduces a different RREQ propagation mechanism in order to compute link disjoint paths that M-DSR cannot find. However, while SMR reduces the number of flooding initiations, SMR doesn t reduce routing overhead considerably. It is because each flooding in SMR requires much more control packets than that of DSR. AOMDV [9] is an AODV-based multipath routing protocol. The RREQ propagation mechanism of AOMDV is same as that of AODV except each RREQ carries an additional field called firsthop to indicate the first hop passed by the RREQ. The firsthop field is used to decide the link disjoint-ness of each RREQ. However, AOMDV also fails to catch many chances to find existing link disjoint paths. It is because the second RREQ is not re-broadcasted. 3 The Proposed Scheme We now describe our Graph-based Multipath Routing protocol based on DSR. First, we explain the basic operation of GMR. We then extend it by considering an optimization method and practical issues. The ideal goal of GMR is to compute all link disjoint paths. But too long paths are not practical because connection on such paths suffers longer end-toend delay. Therefore we focus on only for shortest or sufficiently short paths. When we mention all paths, it means all shortest (or sufficiently short) paths rather than all possible arbitrary hop paths. GMR uses source routing mechanism just like DSR. So a RREQ message contains path information from source node to the intermediate node. But instead of single node list of DSR, each RREQ includes graph information which represents abstract network topology. We call this graph as Reverse Path Graph (RPG). The route discovery process of GMR performed with similar manner to that of DSR. The main difference is that each intermediate node which receives a new RREQ message should wait for some predetermined time to gather more RREQs, if any. If the waiting intermediate node receives more than one RREQ, it merges graph information of those duplicate RREQs with its previous graph

information. After time-out, it re-broadcast one RREQ message which contains all information it gather until that moment. Waiting process enables gathering sufficient route information while it prevents generation more control packets than DSR. It is easy to show that if the time-out interval is sufficient, the re-broadcasted RPG of each node covers all RPGs of the previous hops, that is, all shortest link disjoint paths. If the propagations of RREQ occur simultaneously, the time-out interval needs not to be long. But to prevent collision, wireless MAC layer has back-off process. This makes jitters between RREQ messages. We have chosen 50 milliseconds for the interval, which is larger than MAC layer back-off interval by a factor of magnitude. Waiting some time from the first RREQ, the destination node gathers multiple RREQs. And after time-out, it computes link disjoint paths from the RPG using the local graph search algorithm (e.g. [10]) and it replies to the source through multiple RREPs through multiple paths. Finally, the source uses source routing for data packet delivery. Figure 2 shows the graph information generated during a route discovery process. Fig. 2. The basic operation of GMR. Node 4 receives upper edges from node 1 and lower edges from node 2 while it waits. And node 4 relays fully merged graph to node 6. The limitation on the size of RPG is another control parameter of GMR. If the size goes over one packet size, the number of control packet increases. So one packet size is the loosest bound of RPG size. If an intermediate node detects the merged RPG size exceeds the limitation, it performs following optimization. The optimization occurs by two steps. At first step, from the original RPG, it selects edges which form link disjoint routes form the source node and itself. New RPG is composed of those edges. This process reduces the size of RPG remarkably, but cannot assure that the size falls below the limitation. When the size of new RPG is still larger than the limitation, just one shortest route is computed to

replace RPG. It becomes identical to node list of DSR. This is the second step of optimization. Actually the size of RPG highly depends on implementation of graph information. In the simulation, we used raw edge list implementation, which is one of the worst implementation at the view of graph size. Two IP address compose one edge in RPG. So each edge takes 8 bytes, which look very high overhead. Other proper implementations may reduce the graph size significantly, but we want to show that even with poor implementation, the optimization doesn t affect much over the number of multipaths GMR finds. In the simulations, we limit the size of RPG with 64 edges. 4 Performance Evaluation To compare the performance of GMR with previous work in ad hoc routing, we simulate GMR with DSR and M-DSR. SMR is excluded because it uses more control packets to compute more paths. Also, AOMDV which bases on AODV is not compared with GMR which bases on DSR. We implement the simulator within the ns-2 [11], using the wireless extensions developed at Carnegie Mellon [12]. In our simulation model, 100 mobile hosts are placed randomly within a 1000 meter 1000 meter area and random waypoint model [5] is used as the mobility model. Traffic sources are CBR and the source-destination pairs are spread randomly over the network. There are 10 data sessions and the packet sending rate is 4 packets per second. Each simulation data shown are an average value of ten runs with different randomly generated mobility scenarios. 4.1 Simulation Results Figure 3 shows the number of paths computed by each protocol by a single route discovery process. Through simulations, we limited each protocol to compute at most four paths because more than four paths provide little benefit and make themselves stale routes which may disturb data packet delivery. As expected, DSR computes one path and GMR outperforms M-DSR. It is because GMR provides the destination with more topology information than M-DSR. Figure 3 also proves that M-DSR cannot find existing link disjoint paths even when the number of the paths is fewer than four. This is the basic motivation of GMR and also the basic reason how GMR can outperform M-DSR through the following simulation results. Figure 4 shows the routing overheads of each protocol. Normalized routing load is the ratio of the number of all control packets propagated throughout the whole network and the number of data packets successfully delivered to the destination nodes. Among three protocols, GMR shows the best performance and M-DSR follows. Both surpass DSR. Figure 4 shows the benefit of multipath routing protocols. Even though those three protocols generate almost same number of control packet in one route discovery process, the number of route

Fig. 3. The Number of Computed Paths Fig. 4. Normalized Routing Load

discoveries differs drastically. This benefit glows larger as the mobility increases. So, GMR which computes the most paths shows the least routing overheads. Figure 5 shows how many data packets each protocol delivers successfully. Packet delivery ratio is obtained by dividing the number of data packets correctly received by the destinations by the number of data packets originated by the sources. Two multipath protocols show large difference from DSR in this performance metric. It is because the destination node sends multiple RREPs in multipath protocols while DSR sends only one RREP. In moderately loaded networks, the loss of RREP packets means the failure of the route discovery process. In on-demand protocols, the source uses an exponential back-off algorithm to limit the rate at which it initiates new route discoveries. Since the back-off time is large compared to send buffer capacity, application packets within the back-off time may be dropped due to send buffer overflow. Therefore, multipath protocols which use multiple RREPs shows higher delivery ratio than single path protocols. Between multipath protocols, GMR s delivery ratio is a little higher than that of M-DSR. We think this is because GMR has less routing overheads than M-DSR so network load is lower than that of M-DSR. Fig. 5. Packet Delivery Ratio Figure 6 shows the end-to-end delay of application data packets. As mentioned before, GMR suffers the largest delay in a single route discovery because it uses waiting process. But the end-to-end delay is average delay suffered by all transmitted data packets. So the end-to-end delay of GMR is the least among three protocols. It is because GMR has the least routing overheads so route discovery failures don t happen frequently. If a route discovery fails, data packets in the send buffer are delayed until new discovery finishes. As stated before, the route discovery back-off time is much larger than the route discovery time.

Therefore, GMR which suffers fewer route discovery back-offs shows the shortest end-to-end delay among three protocols. Fig. 6. End-to-end Delay 5 Conclusion We presented the Graph-based Multipath Routing (GMR) protocol for ad hoc networks. Multipath routing schemes try to reduce the number of flooding initiations by searching for multiple paths in a single route discovery. In GMR protocols, each node generates and accumulates the graph data which represents the abstract network topology with distributed manner and relays the graph data toward the destination node. The destination node can use local graph search algorithm to compute link disjoint paths. We have studied the performance of GMR relative to M-DSR and DSR under a wide range of mobility scenarios. We observed that GMR shows the least control packet overhead, the highest packet delivery ratio and the shortest end-to-end delay among three protocols. References 1. C. E. Perkins and P. Bhagwat.: Highly Dynamic Destination-Sequenced Distance- Vector Routing (DSDV) for Mobile Computers. In Proceedings of the ACM SIG- COMM (1994) 234-244 2. D. Johnson and D. Maltz.: Dynamic Source Routing in Ad Hoc Wireless Networks. In T. Imielinski and H. Korth, editors, Mobile computing, chapter 5. Kluwer Academic (1996)

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