# Energy and Environment-Aware Path Planning in Wireless Sensor Networks with Mobile Sink
## 6 Performance Evaluations
### Simulation Results
#### 6.3.1 Network Lifetime Evaluation  
In these experiments, the performance of the proposed algorithm is compared to SEA [18], EGTDA [19], and ACO-based techniques in [22], and EARP [24] for the two situations stated above under varied traffic rate. 1. Network lifetime evaluation under the first scenario  
This experiment studies the variation of network lifetime under environmental conditions inside the normal range. The average traffic rate \(\lambda\) varies from three to nine packets per second throughout this experiment. Figure 6 shows the variation of network lifetime to the average traffic rate under the first scenario. As observed in Figure 6, earlier research [18; 19; 22; 24] using the proposed routing algorithm enhanced network lifetime compared to the PSO-based routing technique in [28] for urgent data collection. As in this scenario, the environmental data are assumed to be in the normal range; thus, the corresponding value of the environmental impact metric is 1. This improvement is because the proposed routing algorithm leverages node traffic load and residual energy to balance network energy usage across sensor nodes. It prevents lost links to save energy wasted retransmitting dropped packets. The PSO-dependent routing method in [28] depends on residual energy to balance energy consumption, which is not adequate according to the observations in this work. It attempts to route data along the quickest path, but a lack of knowledge regarding data transmission reliability wastes energy by retransmitting missed packets. The figure illustrates that our idea boosts network lifetime greatly. These findings are due to the following:  
The suggested route planning takes into account the zone priority and the energy used when moving the mobile sink, which reduces energy use. Consequently, it significantly increases network lifetime. Messages from sensor nodes situated in high priority zones should be relayed right away to the sink node since they are regarded as urgent data. Due to the excessive routing avoidance of urgent data messages and thus lower energy consumption, including zone priority into the path planning choice causes the mobile sink to collect the urgent data from the high priority zones first. Thus, it increases the network's lifetime. The lifetime of the mobile sink is extended by accounting for energy loss during mobility. In order to calculate an energy-saving and target-delay-optimal location, it additionally takes into account the average distance between the mobile sink and urgent data cluster heads. The cluster head selection technique balances network energy use among sensor nodes as a result of the suggested energy measure. To cut down on energy wastage from retransmitting failed packets, it also takes link quality into account when choosing a cluster head. Finally, the proposed routing expands the network's lifetime. Prior studies [18; 19; 22; 24] do not address zone priority in the route planning approach, which leads to greater energy consumption as a consequence of the routing of urgent data messages since the mobile sink would not go to the high priority zone first. They waste resources by retransmitting failed packets during cluster head selection because they are unaware of the dependability of data transfer from member nodes to cluster heads. The methods employed to control energy use are inadequate to achieve an appropriate energy balance, which shortens the lifetime of the network. 2. Network lifetime evaluation under the second scenario  
This experiment studies network lifetime under scenario 2. In this experiment, traffic averages three to nine packets per second. Figure 7 displays the second scenario's network lifetime vs. average traffic rate. The figure indicates that the proposed approach increases network lifetime and traffic rate. As the environmental conditions in this scenario are assumed to be outside the normal range. This is justified as follows:  
Figure 6: Influence of increasing average traffic rate on network lifetime under the first scenario.