# Robust Evolutionary-Game-Based Routing for Wireless Multimedia Sensor Networks
## 5 Performance Evaluation
### Simulation Results and Discussions
Thus, we have excluded QMOR from the performance comparison for the metric of packet delivery ratio. We have calculated the average packet delivery ratio in every 100 s in the simulation time and plotted the graphs for EGR, AB routing, GEEC, EEREG, and LEACH-C. There are multiple sink nodes in EGR; thus, congestion probability is very low in it. EGR had the highest average packet delivery ratio as compared to all the protocols. Figure 19 shows the performance comparison of the five protocols in terms of average packet delivery ratio. The \(X\) axis represents the simulation time and the \(Y\) axis represents the average packet delivery ratio. As shown in this figure, we can observe that EGR outperforms the other four protocols. Even though AB routing and LEACH-C are centrally managed, they do not have any mechanism to select CHs in the network. Therefore, the probability of low energy nodes to become CHs in the network is higher in LEACH-C and AB routing, which eventually may disrupt data transmission causing low data delivery ratio. EGR's biggest advantage is its data redundancy avoidance algorithm along with the multiple sink nodes that not only reduce the redundant transmission of data but also decreases the congestion probability in a great manner. Therefore, it could easily outsmart GEEC and EEREG which do not have any redundancy avoidance mechanism or multisink network architecture. Cluster formation time: If a long time is taken to form clusters, energy consumption can be higher along with network delay. Since WMSNs have stringent requirement for delay and they are formed with energy-hungry devices, it is necessary that the cluster formation takes less amount of time. In Figure 20, \(X\) axis presents the number of nodes and \(Y\) axis presents the cluster formation time in seconds. Cluster formation time is increased as the number of nodes increases for all the protocols. This is obvious because increasing the number of nodes would yield more clusters. As shown in Figure 20, EGR takes lesser amount of time to form clusters compared to other protocols. EGR and  
Figure 15:1 Packet delivery ratio. AB routing form clusters based on the area calculation of the overlapped FoV. EGR takes lesser time than AB routing because EGR can immediately decide to put two nodes in the same cluster, given that the overlapped FoV is a polygon. Both GEEC and EREG have one sink node at the center of the network area. Since the whole network is managed centrally by one sink node for GEEC and EREG, the cluster formation is delayed. On the contrary, EGR could exploit its multisink architecture to build clusters faster. Effectiveness of the data redundancy avoidance algorithm: To prove the effectiveness of the proposed data redundancy avoidance algorithm, we have calculated the network overhead varying the number of nodes in the network. In Figure 21, \(X\) axis represents the number of nodes and \(Y\) axis represents the network overhead in kB/s. First, EGR was implemented without Algorithm 1 and network load was computed by varying the number of nodes starting from 10. In this case, we can observe in Figure 21 that the network overhead is 2205 kB/s for 100 nodes. On the other hand, the network overhead is 1020 kB/s when EGR was implemented with the data redundancy avoidance algorithm. The main reason behind the overhead reduction is the implementation of the redundancy avoidance algorithm that does not allow nodes to capture and transmit the images that are identical to two closely placed nodes. This also reduces the number of transmissions significantly. Figure 15:2 Overhead in EGR implementations with and without Algorithm 1. Figure 15:3 Cluster formation time.