# Robust Evolutionary-Game-Based Routing for Wireless Multimedia Sensor Networks
## 5 Performance Evaluation
### Simulation Results and Discussions  
Average residual energy: Figure 15 shows the decrease of average residual energy of the sensor nodes in different protocols. The \(X\) axis represents the simulation time in seconds and the \(Y\) axis represents the average residual energy. As shown in Figure 15, it can be seen that the energy depleted faster in QMOR than in LEACH-C. This is because QMOR is mainly based on opportunistic routing and maintains a forwarding list of nodes capable of transmitting the data. In QMOR, a set of nodes is selected as potential forwarder. The forwarding candidates that receive the transmitted packet coordinate among each other to decide which of them must forward the packet and which must discard it. This phenomenon is mainly responsible for faster energy depletion. The energy consumption for data both received and transmitted were summed and averaged in each round to calculate the average residual energy. LEACH-C is a cluster-based routing protocol, and there is no such problem of selecting candidate forwarding nodes among which some may even drop data packets. Furthermore, for certain frames, the data is sent to the sink node directly in QMOR which is not energy efficient. Moreover, AB routing uses a simple mechanism of clustering based on the FoVs of the nodes and redundant transmissions are avoided. The protocol is clustering based; thus, number of transmissions are reduced, and it performs better than \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Traffic load & 48 packets/min \\ Packet size & 176 bits (22 bytes) \\ Transmission rate & 2 Mbps \\ Transmission range & 15 m \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Workload parameters. Figure 15: Average residual energy. LEACH-C because of the reduction in redundant transmission avoidance mechanism. Even though GEEC and EEREG has CH election mechanism, they do not provide any kind of data redundancy avoidance technique. EGR, the proposed protocol in this study performs better than the all these five algorithms. The obvious reasons behind this are the inclusion of a more efficient redundancy avoidance algorithm, optimal CH selection using game theory, and inclusion of multiple sink nodes that helped nodes to avoid long distance transmissions. Furthermore, it performs better than AB routing because of the optimal CH election process using EG. If the residual energy of any node \(i\) is \(REi\) at a time \(t\), the average residual energy (for 100 nodes) is calculated using the following equation:  
\[\text{Average residual energy }(t)=\frac{\sum_{i=1}^{100}RE_{i}}{100}. \tag{17}\]  
Network lifetime: Figure 16 shows a comparative graph in terms of the number of living nodes during simulation. The \(X\) axis represents the simulation time and the \(Y\) axis represents the number of living nodes in the simulation time. AB routing performs better than LEACH-C in terms of network lifetime because it has a cluster formation process based on FoV. As mentioned earlier, the network lifetime is considered as the time when half of the nodes are dead. We can see that EGR performs better than the other four protocols when the number of living nodes is 50. The reasons behind this can be summarized as below:  
* EGR uses a unique CH election mechanism based on EG that allows nodes with higher residual energy level to become CHs, resulting in improved energy balance in the network. * Transmission distance from CHs to the sink nodes in EGR becomes shorter in comparison to the other protocols. * Data volume and the number of transmissions have been reduced in EGR. Average end-to-end delay versus the number of nodes: The simulation results were obtained for EGR in terms of end-to-end delay as well. The number of nodes was increased in different rounds and the average end-to-end delay was observed. The delay is lesser in QMOR than that in LEACH-C. The main reason for this is the direct transmission of certain data packets from source node to sink node.