ijcta2011020302

Performance Evaluation of MANET Routing Protocols under CBR and FTP traffic classes

M.L Sharma [email protected] Noor Fatima Rizvi [email protected]

Nipun Sharma [email protected] Anu Malhan [email protected]

Swati Sharma [email protected]

Abstract

Understanding the performance of routing protocols in ad hoc networks is a key feature to determine which routing protocol is best suited for which type of network scenario. From the literature survey it was found that there is a lot of work done on evaluating the performance [3] of various MANET routing protocols for CBR traffic but there is very little work done for variable bit rate like FTP, TELNET type of traffic.

So, in this paper it is proposed to evaluate and analyze the performance of proactive (WRP) and reactive (AODV, DSR) routing protocols based on traffic generators like FTP under different network scenarios like pause time, offered load (i.e. number of source destination pairs), node speed.

Keywords: Ad-Hoc Networks, Performance Evaluation, Packet Delivery Ratio, CBR, FTP

1. Simulation Methodology

Simulation studies have been carried out using GloMoSim [1] network simulator. The modules have been developed using VC++ programming language. GloMoSim is a scalable simulation library for wireless network systems built using the PARSEC simulation environment GloMoSim is designed using a layered approach similar to the OSI seven layer network architecture. Simple APIs are defined between different simulation layers. This allows the rapid integration of models developed at different layers by different people.

2. Performance Metric

In this paper we have worked on Packet Delivery Ratio as the performance metric to evaluate and analyze the performance of various routing protocols.

• Packet Delivery Ratio

Packet delivery ratio is defined as the ratio of data packets received by the destinations to those generated by the sources. This performance metric gives us an idea of how well the protocol is performing in terms of packet delivery at different speeds using different traffic models. Mathematically, we can define as,

M L Sharma,Noor Fatima Rizvi,Nipun Sharma,Anu Malhan,Swati Sharma, Int. J. Comp. Tech. Appl., Vol 2 (3), 392-400

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mailto:[email protected]�




PDR (%) =

� 𝑆𝑆𝑆𝑆𝑆𝑆 𝑜𝑜𝑜𝑜 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑝𝑝𝑑𝑑𝑝𝑝𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝 𝑟𝑟𝑝𝑝𝑝𝑝𝑝𝑝𝑟𝑟𝑟𝑟𝑝𝑝𝑑𝑑 𝑏𝑏𝑏𝑏 𝑝𝑝𝑑𝑑𝑝𝑝ℎ 𝑑𝑑𝑝𝑝𝑝𝑝𝑑𝑑𝑟𝑟𝑑𝑑𝑑𝑑𝑑𝑑𝑟𝑟𝑜𝑜𝑑𝑑𝑆𝑆𝑆𝑆𝑆𝑆 𝑜𝑜𝑜𝑜 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 𝑝𝑝𝑑𝑑𝑝𝑝𝑝𝑝𝑝𝑝𝑑𝑑𝑝𝑝 𝑔𝑔𝑝𝑝𝑑𝑑𝑝𝑝𝑟𝑟𝑑𝑑𝑑𝑑𝑝𝑝𝑑𝑑 𝑏𝑏𝑏𝑏 𝑝𝑝𝑑𝑑𝑝𝑝ℎ 𝑝𝑝𝑜𝑜𝑆𝑆𝑟𝑟𝑝𝑝𝑝𝑝

𝑆𝑆

𝑟𝑟=1

m where, i, indicates the number of output file

m, indicates the total number of output files

3. Simulation Environment

Our simulation considered a network of 50 wireless nodes placed randomly within a 1000 x 1000 m2 area and transmission range of each node is 250 meters. CBR, FTP and TELNET data sessions are chosen. Only a specified number of nodes out 50 will be engaged in data transfer which we specify as offered load. This is done to see the impact of varied load on various performance metrics. However, during this data transfer process all of the 50 nodes will operate in the background for providing necessary support (i.e. routing/forwarding) to the ongoing communication in the network. The rate for CBR traffic is 2 Mbps while the data packet size is 512 bytes. For FTP and TELNET traffic the data rate and packet size is chosen randomly by the simulator which uses a random number generator function to randomly select the number of items to be sent, the size of each item and the size of control packets.

Each simulation is executed for 30 minutes. However, data packets are generated by the sources only during last 800 seconds of simulation time. The initial transient problem illustrates that it requires some time period for nodes to settle down in a MANET and then data transfer actually starts and it is shown that the random waypoint model with zero minimum speed cannot reach a steady state over the course of a simulation, and the level of mobility continuously decreases. This causes the metrics observed to continuously decrease as well. Because of this, time average of these metrics cannot be reliably compared by varying the maximum speed. As we have seen, even under the same maximum speed depending on how long the simulation is run, the resulting average can drastically differ. To avoid initial transient problem and the problem with Random Waypoint Mobility Model RWMM [2], we discard the initial 1000 seconds of simulation period and do not take minimum speed as 0s. Five runs with different seeds have been conducted for each scenario and collected data is averaged over these runs. A summary of salient simulation parameters are presented in Table 3.1.

Table 3.1 Salient Simulation Parameters

Parameter Value

Simulation Time 30 min (1800 sec)

Terrain Area 1000×1000 m2

Number of Nodes 50

Node Placement Strategy Random

Propagation Model Two-Ray Model

Transmission Range of each Node 250 m


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Mobility Model Random-Waypoint

Radio Type Accumulated Noise Model

Network Protocol IP

MAC Protocol IEEE 802.11 DCF

Routing Protocols AODV, DSR,WRP

4. Network Scenarios

In the ad hoc network, we have simulated the following 3 different scenarios:

(a) Pause Time (b) Offered Load (number of source destination pairs) (c) Node Speed

In each of the scenario, unless otherwise specified, simulation settings are same as shown in Table 4.1.

(a) Pause Time

Pause time refers to the rest time of the node. The RWMM includes pause times between changes in direction and/or speed. A node begins by staying in one location for a certain period of time (i.e. a pause time). Once this time expires, the node chooses a random destination in the simulation area and a speed that is uniformly distributed between [MIN SPEED, MAX SPEED]. The node then travels towards the newly chosen destination at the selected speed. Upon arrival the node pauses for a specified time period before starting the process again. In our simulation, we considered 10 m/s as an average node speed, 10 SDPs as offered load, random waypoint as mobility model and 0,500,1000,1500,1800 seconds as pause time. Where, 0s pause time represent the continuous node mobility and 1800s pause time represents static network environment.

(b) Offered Load (Number of SDPs)

Offered load refers to the number of source destination pairs engaged in data transfer. For example, with 10 SDPs amongst 50 nodes, 10 source nodes and 10 destination nodes (i.e. 20 nodes in total) will be engaged in data transfer. However, during this data transfer process, all of the 50 nodes (including the above 20 nodes) will operate in the background for providing necessary support (i.e. routing/forwarding) to the ongoing communication process in the network. In our simulation we considered 10 m/s as an average speed and 0s pause time with offered load (i.e. number of SDPs) varied as 10,20,30,40 pairs.

(c) Node Speed

Node speed refers to the average speed with which nodes move in the simulation area. We have used random waypoint mobility model (RWMM), as it is widely used in MANET simulations [23]. In RWMM, nodes move at a speed uniformly distributed in [MIN SPEED, MAX SPEED]. In our simulation, we have considered 10 SDPs for data transfer and average node speeds considered are 5, 10, 15, 20, 25 m/s. Each node begins the simulation by moving towards a randomly chosen destination. Whenever a node chooses a destination, it rests for a pause time. It then chooses a new destination and moves towards the same. This process is repeated until the end of the simulation time. In this scenario, however, pause time is set at 0s (i.e. nodes move continuously throughout the simulation period). This is


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done to study the impact of continuous node mobility (i.e. worst case scenario) on the network performance.

In this section, we present the results obtained via simulations followed by analysis. Packet delivery ratio, average end-to-end delay, throughput, routing message overhead are the metrics used to evaluate and analyze the performance of reactive (AODV,DSR) and proactive (WRP) routing protocols under different types of traffic like CBR, FTP, TELNET.

5. Results

CBR traffic

Simulation Results

In this section, the simulation results under traffic type CBR for 3 different scenarios, namely, pause time, offered load, node speed are shown.

A. Pause Time Scenario

Packet Delivery Ratio

Figure 5.1 Impact of pause time on packet delivery ratio (CBR traffic)

In Figure 5.1 we observe the impact of pause time on packet delivery ratio. The results show that the packet delivery ratio is maximum when the pause time is equal to the simulation time (i.e. when the nodes in the network are static). The reactive protocol AODV shows the best performance with 99% packet delivery at 1800s pause time. DSR has approximately 30% less delivery ratio than AODV when pause time is less but in a static environment DSR has comparable packet delivery ratio. The WRP being proactive protocol has lesser packet delivery ratio i.e. approximately 60% less delivery ratio than AODV and 20% less than DSR. But in a static network it has a packet delivery ratio of around 73% which shows an increase of more than 30% for pause time 0s with maximum mobility.

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B. Offered Load (Number of Source Destination pairs) Scenario


Figure 5.2 Impact of offered load on packet delivery ratio (CBR traffic)

Figure 5.2 shows the impact of offered load (i.e. number of source destination pairs) on the packet delivery ratio in a network of 50 nodes randomly placed with 0s pause time. The results show that for reactive protocols, AODV and DSR, the delivery ratio degrades with increase in load. The AODV, having a delivery ratio of more than 80% at load of 10 SDPs degrades to less than 70% at load of 40 SDPs. The DSR with delivery ratio of 55% at 10 SDP load degrades to 30% at a load of 40 SDPs. While proactive protocol WRP having the least delivery ratio among the three protocols there is a slight increase in the delivery ratio with load. It has a delivery ratio of 35% at a load of 10 SDPs which increases to more than 40% at a load of 40 SDPs.

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C. Node Speed Scenario

(a) Packet Delivery Ratio

Figure 5.3 Impact of node speed on packet delivery ratio (CBR traffic)

The Figure 5.3 shows the impact of changing the speed, with which nodes move in an ad hoc network, on the packet delivery ratio. In general, packet delivery ratio decreases with increase in average node speed. The packet delivery ratio for AODV is approximately 100% which remains almost same for all node speed. The DSR shows a decrease of 20% in delivery ratio when the average node speed increases from 5 m/s to 25 m/s. The packet delivery ratio for WRP decreases by 13% with increase in node speed. This is because higher speeds cause frequent link changes and connection failures.

FTP Traffic

In this section, the simulation results under traffic type FTP for 3 different scenarios, namely, pause time, offered load, node speed are shown.

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A. Pause Time Scenario


Figure 5.4 Impact of pause time on packet delivery ratio (FTP traffic)

In Figure 5.4, the impact of pause time on packet delivery ratio, for FTP traffic, is shown. The delivery ratio for reactive protocols, namely AODV and DSR is approximately 100%. Both the protocols have almost same delivery ratio at all pause times hence these show the independence of delivery ratio on pause time. On the other hand the delivery ratio for proactive protocol WRP first decreases with increase in pause time and then increases with pause time. The delivery ratio at 0s pause time for WRP is approximately 100% which then decreases to 40% at pause time 1000s and again increases to 80% at pause time 1800s (i.e. when network becomes static).

B. Offered Load (Number of source destination pairs)


Figure 5.5 Impact of offered load on packet delivery ratio (FTP traffic)

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Figure 5.5 shows the impact of offered load (i.e. increasing number of source destination pairs) on packet delivery ratio under FTP traffic. Results show that for all protocols packet delivery ratio is independent of offered load. All the three protocols have approximately same packet delivery ratio when plotted against offered load.

C. Node Speed Scenario Packet Delivery Ratio

Figure 5.21 shows the impact of increasing average speed, with which nodes move, on packet delivery ratio. Results show that the packet delivery ratio is approximately 100% for all the three protocols and does not depend upon node speed.

Figure 5.6 Impact of Average Node Speed on packet delivery ratio (FTP traffic)

6. Conclusion

In this paper, we have simulated the AODV, DSR and WRP routing protocols and evaluated the performance under CBR and FTP traffics. Performance of each routing protocols evaluated using a detailed simulation-based analysis. Performance metrics considered are packet delivery ratio.

From the simulation results, for CBR, FTP and TELNET traffics, we concluded the following:

• For CBR traffic, we have presented 3 different scenarios, varying pause time, offered load (i.e. number of source destination pairs) and average node speed.

In pause time scenario, performance analysis shows that AODV performs better than DSR and WRP in terms of packet delivery ratio, throughput and routing message overhead. WRP exhibits the worst performance in terms of packet delivery ratio, throughput and routing message overhead. But for average end-to-end delay WRP shows the best performance while DSR shows worst performance in terms of average end-to-end delay.

• For FTP traffic, we have presented 3 different scenarios, varying pause time, offered load (i.e. number of source destination pairs) and average node speed.

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In pause time scenario, performance analysis shows that DSR performs better than AODV and WRP in terms of packet delivery ratio and throughput. WRP exhibits the worst performance in terms of packet delivery ratio, throughput and routing message overhead. But for average end-to-end delay WRP shows the best performance while DSR shows worst performance in terms of average end-to-end delay AODV shows the best performance in terms of average end-to-end delay and routing message overhead.

Further Scope

In this section we discuss the further scope of this work.

• HTTP Traffic

In this work, we have evaluated the performance of routing protocols under CBR, FTP and TELNET types of traffic. We can evaluate the performance for web server pages i.e. the HTTP traffic.

• Multimedia Traffic

This work can be extended by evaluating the performance of reactive and proactive protocols under multimedia traffic. Multimedia traffic is the representative of real time scenario. . • Combining different scenarios

In ad hoc networks, we have analyzed the performance in 3 different scenarios namely, pause time, offered load and node speed. Further, we can extend this by combining the different scenarios, for example, varying both pause time and node speed etc. to analyze the performance of each routing protocol. • Considering other scenarios

In ad hoc networks, we have analyzed the performance in 3 different scenarios namely, pause time, offered load and node speed. Further, we can extend this by evaluating the performance by considering other scenarios like transmission range, number of nodes etc. • Including other routing protocols

In ad hoc networks, we have considered the three routing protocols namely, AODV, DSR (reactive) and WRP (proactive) routing protocol. We can extend our work by including other reactive or proactive routing protocols together with some hybrid routing protocols like ZRP.

7. References

[1] L. Bajaj, M. Takai, R. Ahuja, R. Bagrodia. “GloMoSim: A Scalable Network Simulation Environment.” Technical Report 990027, University of California, 13, November 1999.

[2] J. Yoon, M. Liu, B. Noble, “Random Waypoint Considered Harmful,” 0-7803-7753-2/03, IEEE INFOCOM, 2003. [3] Nipun Sharma “ANALYSIS OF SECURITY REQUIREMENTS IN WIRELESS NETWORKS AND MOBILE AD-HOC NETWORKS” GESJ: Computer Sciences and Telecommunications 2010 | No.5(28) [2010.11.30]


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