2007 IEEE International Conference on Signal Processing and Communications (ICSPC 2007), 24-27 November 2007, Dubai, United Arab Emirates

SMS: SHORTEST MULTIPATH SOURCE ROUTINGFOR MOBILE AD-HOC NETWORKS

Haseeb Zafar', David Harlel, Ivan Andonovic', andMahmoodAshraf

Department of Electronic and Electrical EngineeringUniversity of Strathclyde, Glasgow, UK

[haseeb, d.harle, i.andonovic]@eee.strath.ac.uk

2Institute of Communication TechnologiesPakistan Telecommunication Company Limited, Islamabad, Pakistan

mahmood@ictech.edu.pk

ABSTRACT

In recent years, on-demand multipath routing protocolshave been a key research area in mobile ad-hoc networks.Such protocols are crucial in providing resilience to routefailures and to successful load balancing. Previous workshows that on-demand multipath routing protocolsachieve lower end-to-end delay, routing overheads andhigher goodput under certain scenarios when compared totraditional single-path routing protocols. In this paper, theShortest Multipath Source (SMS) routing protocol isproposed. The proposed protocol builds multiple partial-disjoint paths that are shorter when compared to multiplelink-disjoint or node-disjoint paths and, in so doing,reduce end-to-end delay and routing overheads incurredwhen recovering from route breaks. Simulation resultsshow that SMS outperforms the competing protocols withrespect to a number of key performance metrics.

Index Terms- Ad-hoc networks, multipath routing,shortest multipath source routing, partial-disjoint

1. INTRODUCTION

Mobile Ad-hoc Networks (MANETs) [1] are a collectionof wireless mobile nodes that dynamically form atemporary wireless network without an infrastructure. Theprovisioning of real-time multimedia services such asvoice and video over ad-hoc networks is problematicsince wireless links are unreliable and are of limitedbandwidth. Compared to the requirements of data-onlyapplications, these real-time requirements demand highpacket delivery rates, low delays, negligible jitter andlower routing overheads. The design of an efficient andreliable routing protocol for such applications is a majorchallenge.

On-demand routing protocols are credited as beingadaptive to the dynamic environment of MANETs, due totheir low routing overhead and more rapid response toroute failures when compared to their pro-activecounterparts [2-4]. Single-path, on-demand routing

protocols [5-9] rely on a uni-path route for each datasession. In the case of a failure of any active link betweensource and destination, the routing protocol must invoke aroute discovery process and, in so doing, additional delayis incurred and overheads increase. On-demand multipathrouting protocols [10-17] can alleviate these problems byestablishing multiple paths between a source and adestination within a single route discovery process.

The performance of multipath routing protocols oftenstart to degrade in terms of end-to-end delay and routingoverheads when mobility rates and traffic loads increase;a consequence of both longer and stale routes [19].Motivated by such limitations, a Shortest MultipathSource (SMS) routing protocol, an extension to the DSR[5], is proposed that reduces end-to-end delay and routingoverheads incurred when recovering from route breaks.

The rest of the paper is organized as follows.Section-2 presents related work. The Shortest MultipathSource routing protocol is proposed in Section-3. Thesimulation framework based on NS-2 [20] is presented inSection-4. Simulation results are presented in Section-5and concluding remarks are made in Section-6.

2. RELATED WORK

On-demand multipath routing protocols are useful forfinding more than one possible route between a sourceand a destination. Several different multipath routingprotocols based on source routing have been proposed.

Multipath-DSR (M-DSR) [10] is a simple extensionof the popular DSR Instead of replying on the firstreceived route-request as in DSR, the destination nodesends an additional route-reply for a route-request whichcarries a link-disjoint route compared with the routesalready replied. However, in many cases, M-DSR cannotcompute link-disjoint paths because the intermediatenodes drop every duplicate route-request that may invokeanother link-disjoint path.

Multipath Source Routing (MSR) [11] extendsDSR's route discovery and route maintenance phases tocompute multiple node-disjoint paths which are used

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simultaneously to distribute traffic. It proposes amechanism to distribute load over multiple paths, basedon the round-trip time measurement in such a way thatpaths with lower delay receive a greater proportion oftraffic. Such an approach has the disadvantage, pertinentto multimedia services, that traffic flows over the differentpaths may be unbalanced and requires re-sequencing andincurs additional delay at the receiver.

The Split Multipath Routing (SMR) [12] protocol isan on-demand multipath source routing that provides away of determining maximally disjoint paths. It uses amodified route-request packet flooding scheme in theroute query process. This approach has the disadvantageof transmitting a large number of route-request packets.

Graph-based Multipath Routing (GMR) [14]generates the network topology graph to compute all link-disjoint paths in the network. Unlike DSR, eachintermediate node receiving a new route-request messagewaits for some predetermined time to gather further route-requests, if any. If the waiting intermediate node receivesmore than one route-request, it merges graph informationfrom those duplicate route-requests with its previousgraph. The limitation ofGMR is the delay and the size ofreverse path graph.

3. SHORTEST MULTIPATH SOURCE ROUTING

We propose a novel and practical on-demand multipathrouting protocol called Shortest Multipath Source routingprotocol (SMS). The protocol modifies and extends DSR[5], to build multiple partial-disjoint paths from source todestination in order to avoid the overhead of additionalroute discoveries and to recover quickly in case of routebreaks. Thus, improved performance in terms of goodputand end-to-end delay is obtained.

SMS computes shortest multiple partial-disjoint pathsthat will bypass at least one intermediate node on theprimary path. For example, in Figure 1, the paths S-A-F-C-D, S-E-B-C-D and S-A-B-J-D are partial-disjoint pathscompared to the primary path S-A-B-C-D. Partial-disjointpaths are different from both link-disjoint and node-disjoint multiple paths, in the sense that partial-disjointpaths can have both nodes and links in common. This lessrestrictive constraint allows the computation of morepartial-disjoint paths than node-disjoint or link-disjointmultiple paths and provides a better fault-tolerance in thesense of faster and efficient recovery of route breaks. Thissection describes route discovery phase, route replyphase, selecting partial-disjoint paths and routemaintenance phase of the proposed algorithm.

Fiue atildsjitmutpe ahFigure I Partial-disj'oint multiple paths

3.1. Route Discovery Phase

When a node seeks to communicate with another node, itsearches its cache to find any known routes to thedestination. If no routes are available, the node initiatesroute discovery by flooding route-request (RREQ)packet, containing an ID which, along with sourceaddress, uniquely identifies the current discovery. TheSMS scheme modifies the approach to reduce broadcastoverhead introduced in NDMR [15]. When a nodereceives a RREQ packet for the first time, it checks theroute path from the packet and calculates the number ofhops from the source to itself and records the number asthe reverse shortest hop count in its cache. If the nodereceives the RREQ duplicate again, it computes thenumber of hops from the source to itself and comparesthis number to the reverse shortest hop count recorded inits cache. If the number of hops is less than or equal to thereverse shortest hop count, the node appends its ownaddress to the route path list of the RREQ packet andbroadcasts the RREQ packet to its neighboring nodes.Otherwise, the node drops the RREQ packet.

For example, in Figure 2, when node A receives theRREQ packet at the first time from path S-A, it records 1as the reverse shortest hop count in its cache. When thenode A receives a duplicate RREQ from E and H, itcalculates the number of hops and compares the currenthop count to the reverse shortest hop count in its cache.As the current hop count is greater than the reverseshortest hop count, the duplicate RREQ packet isdiscarded.

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Figure 2 Reducing broadcast overhead

3.2. Route Reply Phase

When the node receives the RREQ packet, it generates aroute-reply (RREP) packet to the source using the reversepath identified within the RREQ. In addition, the noderecords the reverse path within its internal cache. Uponreceiving multiple copies of RREQ packets of the samesession, the node sends limited replies to avoid a replystorm; the number of RREPs has been limited to fivealthough more than five RREPs can be sent. These newpaths are also appended to the internal cache.

3.3. Selecting Partial-Disjoint Paths

In the algorithm of selecting partial-disjoint paths, thesource is responsible for selecting and recording multiplepartial-disjoint route paths. An example that illustrates theselection of partial-disjoint paths is shown in Figure 3.

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Consider the case of traffic flowing between nodes S andD using link S-A-B-C-D as primary path. In case of a linkfailure between A-B, the source node will search thecache for an alternate route that does not contain node B.The path S-A-F-C-D is selected randomly from thecandidate paths S-A-F-C-D and S-H-I-C-D.

C~~~~~ .<... .........SAFCD /

SEBCDAC D

SABJD

SHICD

Figure 3 Selection of alternative path in case of link failure

3.4. Route Maintenance Phase

In the event of a link failure or an intermediate nodemoving out of range, a route-error (RERR) packet istransmitted. The reception of a RERR packet willinvalidate the route via that link to that destination andwill switch to an alternative path if available. The sourcenode will then select an alternative path from thecandidate paths. When all routes in the cache are markedas invalid, the node will delete the invalid routes and anew route discovery is instigated.

4. SIMULATION FRAMEWORK

Network simulator NS-2 [20] is used to execute theproposed SMS protocol and contrasted with DSR [5] andSMR [12]. The simulation environment consists of 50wireless nodes forming an ad-hoc wireless network,moving over a 700m x 500m flat space. The physicalradio model uses the characteristics of the 914MHzLucent WaveLAN direct sequence spread spectrum radiowith minimal range of 250m and nominal bit rate of2Mbps. The distributed co-ordination function (DCF) ofIEEE802.11 is used as the MAC, a carrier sense multipleaccess with collision avoidance technique (CSMA/CA).An Interface Queue (IFQ) is used to queue all routing anddata packets at the routing layer (until the MAC layer cantransmit them). The IFQ has a maximum size of 50packets, maintaining a queue with two priorities eachserved in a first-in first-out (FIFO) order. Routing packetsare assigned a higher priority than data packets.

4.1. Traffic and Mobility Models

Random constant bit rate (CBR) traffic connections andtransmission control protocol (TCP) are establishedbetween mobile nodes using a connection patterngenerator script [20]. Traffic sources are CBR sourcesgenerating 512 byte data packets at a rate of 4 packets persecond with a pause time of 30 seconds. The number ofsources is varied to change the offered load in thenetwork. Mobility is characterized by varying velocities ata simple random waypoint model, which can be setup

using a scenario generator script [20]. Simulations are runfor 500 simulated seconds. Each data point represents anaverage of ten runs using different seeds with thecorresponding confidence interval of 95% [18].

4.2. Performance Metrics

Three key performance metrics [9] are evaluated:

* Goodput: the ratio of the data packets delivered todestinations to those generated by the CBR sources.

* Average End-End Delay: includes all possible delayscaused by buffering during route discovery, queuingat the interface queue, re-transmission delays at theMAC, propagation and transfer times.

* Normalized Routing Load: the number of routingpackets transmitted per data packet delivered at thedestination. Each hop-wise transmission of a routingpacket is counted as one transmission.

5. SIMULATION RESULTS

The set of experiments varies the number of sources witha random velocity of 0-10 m/s for 50 nodes. The networkload is varied by changing the number of active sourcesbetween 10 and 40 with a fixed rate of 4 packets persecond and a pause time of 30 seconds.

Goodput: The goodput of the three protocols isshown in Figure 4, showing that the value of this metricfor SMS is significant compared to both SMR and DSRprotocols. Although the goodput of SMS is more than80%, it decreases more quickly with larger numbers ofsources, the reasons being more collisions in the air andcongestion in node buffers. SMR produces a largenumber of control packets which overloads the networksignificantly.

Average End-to-End Delay: The average end-to-enddelay as a function of the number of sources is shown inFigure 5. It can be seen that SMS has a lower averagedelay than both SMR and DSR under the majority ofvalues. Although SMS has shortest alternative routingpaths, its delay also increases gradually with an increasein the number of sources. Because of the limitations of aconstrained wireless bandwidth, packets that will beforwarded must wait longer in buffers to access anavailable radio channel and avoid collisions.

Normalized Routing Load: The normalized routingload of the three protocols is shown in Figure 6, showingthat the value of this metric for SMS is significant whencompared to SMR. With the increase of the number ofsources, the probability of packet collision and packetcongestion increases, leading to an increase of normalizedrouting load. DSR has the lowest value; multipathprotocols generate more control packets while buildingmultiple routes. While DSR builds single route for eachsession and minimizes flooding overhead by allowingintermediate nodes of replying from cache.

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10 15 20 25 30 35 40

Number of Sources

Figure 4 Goodput vs. Number of Sources

10 15 20 25 30 35 40

Number of Sources

Figure 5 Average End-to-End Delay vs. Number of Sources

2.5

2

10 15 20 25 30 35 40

Number of Sources

Figure 6 Normalized Routing Load vs. Number of Sources

6. CONCLUSIONS

Most of the protocols proposed achieve goodput, averageend-to-end delay and routing overheads at certainmobility and offered load. To improve performance interms of delay bounds or guarantees and higher goodput,a modified protocol referred to as SMS is proposed. SMSreduces end-to-end delay significantly by recording themultiple shortest loop-free paths. It is evident fromsimulation results that SMS performs better than bothDSR and SMR when considering a number of metrics andis a candidate that, potentially, offers improved routingperformance.

7. REFERENCES

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[20] The VINT Project. The Network Simulator - NS-2,http://www.isi.edu/nsnam/ns/

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