Traffic Pattern Based Performance Comparison of Two Reactive Routing Protocolsfor Ad Hoc Networks Using NS2

Suresh Kumar, R K RathyDepartment of Computer Science and EngineeringCareer Institute of Technology and Management

Faridabad, Indiae-mail: enthusk@yahoo.com, rathy.citm@yahoo.co.in

Diwakar PandeyDepartment of Computer Science and Mathematics

CCS University, Meerut, Indiae-mail: pandey_diwakar2k1@rediffmail.com

Abstract— Ad hoc networks are characterized by wirelessconnectivity, continuous changing topology, distributedoperations and ease of deployment. Routing in Ad hocnetworks is a challenge due to mobility and thus is a currentarea of research. We compare two reactive routing protocolsby considering multiple performance metrics to bring out theirrelative merits. Both DSR and AODV share similar on demandbehavior, but the protocols internal mechanism leads tosignificant performance differences. We have analyzed theperformance of protocols by varying network load, mobilityand type of traffic (CBR, TCP). A detailed simulation has beendone using NS2. We consider packet delivery fraction,normalized routing load, average delay, routing overhead, andpacket loss as metrics for performance analysis of theseprotocols.

Keywords- AODV, DSR, Performance, Mobility, RoutingAd-hoc Network, Routing

I. INTRODUCTION

Ad-hoc network is a collection of wireless mobile nodesforming a temporary network without any existing wire-lineinfrastructure. Communication between nodes is based onradio to radio multi-hoping. Ad-hoc networks arecharacterized by frequent topology change due to mobilityof nodes. Nodes may join and leave the network at any time.Wireless network systems have gained importance in recentyears by combining the potentiality of large number ofcomputers situated at different places in a continuouslymoving environment. All nodes in such networks behave asrouters and take part in discovery and maintenance of routesto the other nodes in the network. Ad hoc networks have todeal with many challenges and the one that is mostimportant is route selection. So the routing algorithm mustbe dynamic and must be adaptive to the frequent topologychanges due to node mobility. Many algorithms have beenproposed in the literature that can be used in ad hocnetworks for finding routes [1][2][3]. Availability of lowcost wireless devices and vast application areas of ad hocnetworks has encouraged researchers to develop new andefficient routing protocols. In this paper we presentperformance comparison of two reactive routing protocolsDSR [1] and AODV [2] to bring out their relative merits.Both are on demand protocols and they initiate their routingactivities only when required. The motivation behind this

comparison is to understand their internal workingmechanism and bring out situations where one is preferredthan the other.

II. ROUTING PROTOCOLS PERFORMANCEISSUES

Routing is defined as the process of finding a path from asource to some arbitrary destination on the network. Mobilead hoc networks, or MANET, are fundamentally differentfrom traditional wired networks as wired networks areassumed to be stationary and static. So the routing protocolsdesigned for wired networks can’t work efficiently in Adhoc networks. This imposes different design requirementand constraints on routing protocols for MANET.International MANET working group has defined someunique characteristics of ad hoc networks in RFC 2501 [4].These properties do not directly relate to performance, butthey describe very nature of ad hoc networks and formulateboundary conditions of ad hoc networks. To measureexternal performance of a protocol, we consider throughputand end-to-end delay as metrics and to measure internaleffectiveness of a protocol; we consider routing overhead,normalized routing load, packet delivery ratio and averagehop count as the metrics.

Throughput: It gives the fraction of the channel capacityused for useful transmission (Data packets correctlydelivered to the destination) and is defined as the totalnumber of packets received by the destination. It is in fact ameasure of the effectiveness of a routing protocol.Average end-to-end delay: This includes all possible delayscaused by buffering during route discovery latency, queuingat the interface queue, retransmission delays at the MAC,and propagation and transfer times.Routing overhead: It is the total number of routing packetstransmitted during the simulation. For packets sent overmultiple hops, each transmission (per hop) is considered asone transmission. All the packets sent or forwarded atnetwork layer is considered as routing overhead.Normalized routing load (NRL): NRL is the number ofrouting packets transmitted per data packet delivered at thedestination. Each hop-wise transmission of a routing packet(forwarded) is counted as one transmission. This metric is

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highly correlated with number of route changes occurred inthe simulation.Packet delivery fraction: The ratio of the data packetsdelivered to the destinations to those generated by the trafficsources.Packets loss: Packet loss is a measure of the number ofpackets dropped by the routers due to various reasons.

All these metrics are most widely used for representingperformance of routing protocols because higher datadelivery, lower control overhead and lower delay are alwaysdesirable. The essential parameters, which we have varied inour simulations, are mobility, network size and node-connectivity.

III. RELATED WORKSeveral performance evaluations of MANET routingprotocols using CBR traffic have been done in the literature[6,10,12,13] by considering various parameters such asmobility, network load and pause time. Arun B. R et al. [12]have analyzed the performance of various protocols usingVBR traffic in Ad-hoc networks and have shown thatreactive protocols performs better than proactive protocols.Chandershekher [11] analyzed the performance of variousrouting protocols for ad-hoc networks using TCP traffic fora limited scenario. Das S R et al. [13] analyzed theperformance of both DSR and AODV using CBR traffic byvarying network load, mobility and pause time, similar towhat we have done.

IV. SIMULATION SETUPFor simulation we have used NS-2[5] developed byMonarch Research Group in CMU [7]. It has the support forsimulating multi hop wireless networks. The protocolsmaintain a send buffer of 64 packets. It contains all datapackets waiting for a route, such as packets for which routediscovery has started but no reply has arrived yet. Toprevent buffering of packets infinitely, packets are droppedif they have to wait in the send-buffer for more than 30s. Allpackets (both data and routing) sent by the routing layer arequeued at the interface queue until the MAC layer cantransmit them. The interface queue has a maximum size of50 packets and is maintained as a priority queue with twopriorities each served in FIFO order. Routing packets gethigher priority than data packets.We have generated 50 scenarios (5 for each pause time) andfour traffic patterns with varying number of sources for eachtype of traffic (CBR and TCP). The simulation is run usingthese scenarios and traffic patterns for both these protocols.To overcome the effect of randomness in the output we havetaken the averages of the results to get their realistic values.The goal of our simulation is to evaluate the performancedifferences of these two reactive routing protocols. We havevaried mobility and the number of sources to measure their

performance. Simulations are carried out by varying thenumber of traffic sources as 10 and 40. The pause time isvaried from 0sec (high mobility) to 900sec (no mobility) inan interval of 100sec. The simulation results reveal someimportant characteristic differences between the routingprotocols. The presence of high mobility implies frequentlink failures and each routing protocol reacts differentlyduring link failures. The different basic internal workingmechanism leads to the performance differences in the seprotocols

A. Simulation Parameters and Mobility ModelsWe have done simulations of all the scenarios for 900simulated seconds in a rectangular field of 1500mX300mwith 50 nodes and varying the degree of connectivity amongnodes. The source-destination pairs are spread randomlyover the network. The size of data packets is 512 bytes.Varying the number of sources and the data-rate changes thetraffic load in the network. The random waypoint model [6]is used as the mobility model for the simulation. In thismodel, each node starts its journey from a random locationto a random destination with a randomly chosen speed(uniformly distributed between 0–20m/s). Once thedestination is reached, another random destination istargeted after the specified pause time. The pause time,which affects the relative speeds of the mobile nodes, isvaried from 0sec to 900sec (0 means continuously movingand 900 means stable). When the nodes are continuouslymoving (0sec pause time) the number of link changes arevery high and decreases with increase in pause time andconverge to 0 (900sec pause time). At this stage the networkbecomes stable. The simulation parameters are shown inTable 1.

Table 1: Simulation ParametersS. No. Parameter Value

1 Routing Protocols DSR, AODV

2 MAC Layer 802.11

3 Terrain Size 1500mX300m

4 Nodes 50

5 Node Placement Random

6 Mobility Model Random Waypoint

7 Data Traffic CBR, TCP

8 Simulation Time 900s

9 No. of Sources 10,40

10 Pause Time 0-900 (intervals of 100)

11 Speed 0-20m/s

V. EXPERIMENTAL RESULTS ANDPERFORMANCE COMPARISION

Packet Delivery: In case of CBR traffic both the protocolsdeliver almost all the originated data packets when nodemobility is low (i.e., at large pause time) and the number ofsources is kept small (say at 10), converging to 100%delivery when there is no node motion (Figure 1). But thedelivery rate starts decreasing when there is increase in thenumber of sources and goes down up to 30% when thenumber of sources is large (say at 40). For TCP traffic thereis significant difference in the performance of DSR andAODV (Figure 2). DSR perform better irrespective of thenetwork load.

Normalized Routing Load: For CBR traffic, DSR protocolhave significantly lower routing load than AODV (Figure 3),with the factor increasing with a growing number of sources.We observe that, when the number of sources is low, theperformance of DSR and AODV is similar regardless ofmobility. But with large numbers of sources, DSR startsoutperforming AODV for high-mobility scenarios. Further,DSR always have a lower routing load than AODV.

CBR Traffic Sources

Packet Delivery Fraction (%)

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0 100 200 300 400 500 600 700 800 900

P ause T i me (sec)

DSR10 AODV10 DSR40 AODV40

Figure 1: Packet Delivery Fraction vs Pause Time

Normalized Routing Load

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0 100 200 300 400 500 600 700 800 900Pause Time (sec)

NR

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DSR10 AODV10 DSR40 AODV40

Figure 3: Normalized Routing Load vs Pause Time

The trace files of NS-2 indicate that the major contributionto AODV routing overhead is from route requests packets,

whereas in DSR route replies contribute to large fraction ofrouting overhead. But for TCP traffic, performance ofAODV is better as routing overheads for DSR is more forthis type of traffic as shown in Figure 4.

Average end-to-end Delay: Average delay in DSR iscomparable to AODV when the number of sources is small.But with the increase in the network load (number ofsources), delay in DSR becomes at least double as comparedto the delay in AODV for both types of traffic (Figure 7 and8).

Packet Loss: For CBR traffic, when the number of sourcesis small the packet loss is comparable (Figure 9). But withthe increase in the network load the packet loss in DSR isless as compared to AODV. The reason appears to be thatDSR always has more than one route for a destination. Ifone route fails, then route discovery is not started and thepacket is sent using alternate route. But for TCP traffic thepacket loss is more in less stressful environment for both theprotocols (Figure 10).

TCP Traffic Sources

Packet Delivery Fraction(%)

9596

9798

99100

101

0 100 200 300 400 500 600 700 800 900

Pause T i me(sec)

DSR10 DSR40 AODV10 AODV40

Figure 2: Packet Delivery Fraction vs Pause Time

Normalized Routing Load

0

0.5

1

1.5

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DSR10 DSR40 AODV10 AODV40

Figure 4: Normalized Routing Load vs Pause Time

Routing Overheads

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20

40

60

80

100

0 100 200 300 400 500 600 700 800 900

Pause T i me(sec)

DSR10 AODV10 DSR40 AODV40

Figure 5: Routing Overheads Load vs Pause Time

Average E-E Delay(ms)

02000400060008000

1000012000

0 100 200 300 400 500 600 700 800 900Pause Time(sec)

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ay(m

s)

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DSR10 AODV10 DSR40 AODV40

Figure 7: Average End-End-Delay Load vs Pause Time

Packet Loss(%)

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0 100 200 300 400 500 600 700 800 900Pause Time(sec)

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Figure 9: Packet Loss Load vs Pause Time

Routing Overheads

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0 100 200 300 400 500 600 700 800 900Pause Time(sec)

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ting

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Figure 6: Routing Overheads Load vs Pause Time

Average E-E Delay (ms)

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0 100 200 300 400 500 600 700 800 900Pause Time(sec)

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Figure 8: Average End-End-Delay Load vs Pause Time

Packet Loss (%)

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0 100 200 300 400 500 600 700 800 900Pause Time(sec)

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DSR10 DSR40 AODV10 AODV40

Figure 10: Packet Loss Load vs Pause Time

VI. CONCLUSIONDSR and AODV both use on-demand route discovery, butwith different routing mechanics. The general observationfrom the simulation is that for application-oriented metricssuch as packet delivery fraction and delay, AODVoutperforms DSR in stressful situations (high load and/orhigh mobility), with widening performance gaps withincreasing stress (more load and, high mobility). DSRprotocol, however, consistently generates less routing loadthan AODV for CBR traffic scenarios. But it has beenobserved that for TCP traffic scenarios, performance ofAODV is much better than DSR. In summary, it can be saidthat for robust scenario where mobility is high, area is large,the amount of traffic is more and network is for longerperiod, AODV performs better. For the normal situationswhere a network is of general nature with moderate trafficand moderate mobility, DSR would be the right choice forUDP applications, as it delivers more packets at thedestination with lowest routing overheads. For TCPapplications AODV is found to be a better choice.

Further, we find that for our results are comparable withthose obtained by Das S R [13] for CBR traffic. We haveanalyzed much large scenario than analyzed byChandershekher [11] for TCP traffic. Our results give muchcloser view of the performance of the protocols for packetdelivery fraction, average delay, and packet loss metricsthan by them.

We can further do more rigorous simulations to obtain betterunderstanding of these protocols in more diverse conditions,which may subsequently helps in the development of newprotocols or modification in the existing protocols foroptimum deployment in application specific scenarios. Ourfuture work will include the modification of DSR andAODV to reduce the routing overhead for the performanceoptimization.

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