# Bio-Inspired Energy-Efficient Cluster-Based Routing Protocol for the IoT in Disaster Scenarios
## 7 Simulation Results
However, the proposed model performed much better than the LEACH and DEEC models, with the residual energy lasting until after 1957 rounds. On the other hand, for Scenario 2, the residual energy for LEACH, DEEC, and PSO depleted at 967, 1187, and 1325 rounds, respectively. However, the proposed model lasted until 1600 rounds. The LEACH model experienced higher energy consumption due to the random selection of CHs and single-hop data transmission. For the DEEC algorithm, the optimal distance is not considered when selecting CHs. The PSO model considers the residual energy and distance to the BS but does not consider the distance between CHs and orphan nodes. The proposed model performed better as it considers higher residual energy, distance, and orphan nodes, thereby extending the network's lifetime. Figures 8 and 9 show the network performance throughput for the proposed model compared with that of the LEACH, DEEC, and PSO models for Scenario 1 and Scenario 2, respectively. The throughput was also measured by changing the number of nodes. In both scenarios, the proposed model's network throughput was significantly higher than that of the other protocols. The proposed model achieved a throughput increase of 10 to 20% compared to the other models. This can be attributed to the proposed model's fitness  
Figure 6: Residual energy for Scenario 1. Figure 7: Residual energy for Scenario 2.  
function, which reduces energy consumption during data transmission to achieve a higher network throughput. Figure 10 shows the total packets received by the BS. Scenario 2 considered 200 nodes for this evaluation. More than 18,000 packets were received by the BS for the proposed model. However, the LEACH and DEEC models could not send as many packets compared to the PSO model. The proposed model sent over 12,000 more packets than the LEACH and DEEC models and 4000 more packets than the PSO model. The reason for this is that the proposed model's fitness function preserves the nodes' residual energy, which extends their lifetime. This enhances network lifetime and increases the number of packets transmitted to the BS. Figure 11 shows the packet-drop ratio for Scenario 2 with varying numbers of nodes. The proposed model achieved a lower packet-drop ratio compared to the other models. The LEACH and DEEC models had significantly higher packet-drop ratios for different node numbers compared to the proposed model. The packet-drop ratio for the proposed model increased by approximately 5% with the addition of 100 nodes. The proposed fitness function helps minimise data transfer drops as the model selects energy-efficient paths to send the data. However, the PSO model achieved a lower drop ratio because of the routing efficiency. Nevertheless, due to the inefficient selection of CHs and routing paths, the LEACH and DEEC models achieved higher packet-drop ratios. Figures 12 and 13 show the percentage improvement in network lifetime for the proposed model in Scenario 1 and Scenario 2, respectively. The proposed model is compared with the state-of-the-art PSO and hybrid models. The proposed model significantly improved network lifetime, increasing by 27%, 24%, and 21% in Scenario 1 for 100, 200, and 300 nodes, respectively. In Scenario 2 (Figure 13), the proposed model achieved increases of 23%, 21%, and 17% for 100, 200 and 300 nodes. The proposed model achieved a higher network lifetime compared to the other state-of-the-art models, with the network lifetime increasing by approximately 10%. This is  
Figure 8: Throughput comparison of different nodes for Scenario 1. Figure 9: Throughput comparison of different nodes for Scenario 2.