Impact of Network Density

In this section the performance impact of network density on the three protocols is examined. The network density has been varied by changing the number of nodes placed in a 1000m x 1000m area of each simulation scenario. Each moves with a random speed chosen between 0 and 20m/sec. For each simulation trial, 10 identical random source-destination pairs are used.

Routing Overhead:

Figure 4.3 illustrates the routing overhead generated by the three routing protocols when the number of nodes is varied. The figure shows that the generated routing overhead in all the three routing protocols increases with increased number of nodes. Moreover, the figure reveals the clear advantage of FF-AODV over AODV and FP-AODV. For instance, compared with the AODV and FP-AODV, the generated routing overhead in FF-AODV can be reduced by approximately 30% and 84% respectively when the number of nodes is relatively small (e.g. 25 nodes). The performance advantage of FF-AODV over the FP-AODV and AODV is further increased in dense networks. For example, in figure 4.3, when the number of nodes is increased to 225 nodes, the generated routing overhead in FF-AODV could be reduced by as much as 73% and 140% less than FP- AODV and AODV respectively.

Figure 4.3. Routing overhead versus number of nodes placed over 1000m x 1000m area.

Collision Rate:

Figure 4.4 depicts the number of packet collisions experienced at the MAC per second as the number of nodes increases. It can be seen in the figure that the performance behaviour of the three routing protocols in terms of average collision rate is similar to the routing overhead reported in Figure 4.3. Since data and control packets share the same broadcast wireless medium, the collision rate is high when there are a large number of nodes in the same coverage area transmitting packets at the same time.

The figure also reveals that as the number of nodes increases the superiority of FF-AODV over the FP-AODV and AODV becomes more prominent, confirming the scalability support of the FF-AODV algorithm. When the FF-AODV is used, the probability of two more nodes transmitting at the same time is significantly reduced, because of the fact that most of the nodes outside the active zone have been made to probabilistically suppress their broadcasts. For example, Figure 4.4 shows that the collision rate of FF-AODV could be reduced by approximately 100% and 250% under 225 nodes when compared against the FP- AODV and AODV, respectively.

Figure 4.4. Average collision rate versus number of nodes placed over 1000m x 1000m area.

Normalised Network Throughput:

Figure 4.5 depicts the achieved network throughput of all three protocols against network density. Although significant savings on routing overhead is achieved by the probabilistic protocols, the normalised network throughput achieved by the probabilistic protocols is low for both sparse and dense networks. This is due to the fact that in a sparse network (e.g. 25 nodes) most of the nodes are outside the transmission range of each other, causing partitioning in the network. As a consequence some of the RREQ packets failed to reach their respective destinations. On the other hand, in a dense network, the more than optimal number of RREQ packets is disseminated causing an increase in the channel contention and packet collisions, thereby reducing the available bandwidth of actual data communication. As can be seen in Figure 4.5, the network throughput of FF-AODV could be increased by as much as 30% and 70% when compared against AODV and FP-AODV in a relatively dense network (e.g. 225 nodes).

The network connectivity success ratio which measures the percentage of the number of route discovery processes that succeed in finding a route in the three protocols is shown in Figure 4.6. Similar to results in Figure 4.5, the connectivity success ratio in each of the protocols increases to a maximum and drops as the network density increases. The figure also depicts that the simple flooding

basing AODV outperforms both the FF-AODV and FP-ADV when the density is relatively low (e.g. 25 nodes). However, in a relatively dense network (e.g. 225 nodes), the FF-AODV performed approximately 10% and 20% better than the FP- AODV and AODV respectively.

Figure 4.5. Normalised network throughput versus number of nodes placed over 1000m x 1000m area.

Figure 4.6. Connectivity success ratio versus number of nodes placed over 1000m x 1000m area.

End-to-End Delay:

The results in Figure 4.7 illustrate the performance of the three routing protocols in terms of end-to-end delay when the number of nodes in the network is varied. In on-demand route discovery, data packets at the source node are often queued until a route to the destination is established. Therefore, if the

time used to discover the route is relatively longer, then the total time required to transmit the data packets from source to destination is increased. As shown in figure 4.7, the delay incurred by each of the three routing protocols decreases to a minimum when the number of nodes is increased from 25 to 100 nodes and increases after reaching a minimum value as the number of nodes increases from 100 to 225 nodes. The poor performance of the three protocols in a relatively sparse network is due to the poor network connectivity associated with sparse networks.

The figure also reveals that high channel contentions, congestion and packet collisions resulting from a dense network (e.g. 225 nodes) could degrade the end-to-end delay of the protocols. The results in Figure 4.7 show that, in a dense network, FF-AODV outperforms FP-AODV and AODV by reducing the delay by approximately 53% and 85% respectively. This is because the contention for the communication channel and the packet collisions are reduced as a result of a reduction in the routing overhead.

Figure 4.8 depicts the performance of the three routing protocols in terms of route discovery delay over varying network density. The performance comparison in terms of route discovery presents similar performance trend as end-to-end delay shown in Figure 4.7. FF-AODV performs poorly in sparse networks. However, in a relatively dense network, FF-AODV outperforms the AODV and its fixed probabilistic variant.

Figure 4.8. Route discovery delay versus number of nodes placed over 1000m x 1000m area.