# Network Lifetime Improvement through Energy-Efficient Hybrid Routing Protocol for IoT Applications
## 4 Proposed Hybrid PSOGA
### Proposed Hybrid-Based PSOGA Routing
Furthermore, Figure 8c illustrates increases in the alive nodes by 236.7% and 5.89% when compared to LEACH and PSO, respectively. The PSOGA showed significant improvements in the residual energy by 301% and 7.9% compared to LEACH and PSO, respectively (Figure 8d). PSOGA also showed substantial improvements in the PDR by 274.7% compared to LEACH and PSO, respectively. 46.92% compared to PSO (Figure 8e), and the throughput of the network with the PSOGA increased by 54.82% and 6.98% as compared to LEACH and PSO, respectively (Figure 8f). Figure 6: Results of Case study 3: 4 \(\times\) 4, 200 nodes. (**a**) Network structure for Case Study 3. (**b**) Packets reaching the BS. (**c**) Total alive nodes. (**d**) Total residual energy. (**e**) PDR. (**f**) Throughput. Figure 7: Results of Case Study 4: 10 \(\times\) 10, 625 nodes. (**a**) Network structure for Case Study 4. (**b**) Packets reaching the BS. (**c**) Total alive nodes. (**d**) Total residual energy. (**e**) PDR. (**f**) Throughput. Figure 8: Results of Case Study 5: 10 \(\times\) 10, 1250 nodes. (**a**) Network structure for Case Study 4. (**b**) Packets reaching the BS. (**c**) Total alive nodes. (**d**) Total residual energy. (**e**) PDR. (**f**) Throughput. In Case Study 5, with 1250 nodes and 100 grids, the performance of the network improved as compared to Case Study 4. The number of packets sent to the base station was \(3.2\times 10^{6}\), which is higher than in the previous case study. Similarly, the PDR was also enhanced to 65% from the 60% achieved in Case Study 4. The throughput achieved in Case Study 5 was 17,000, higher than the 15,500 achieved in Case Study 4. The enhancement in the performance metrics can be attributed to the structure, where, although the number of grids is higher, the higher number of nodes--1250--sustained the network for a longer time and, thus, enhanced the performance metrics of the network. ### Comparative Analysis

The results over various node densities and varying network grids were analyzed and the comparative data of the network lifetime are presented in Figure 9. The first node dead (FND), half node dead (HND), and last node dead (LND) were the metrics of comparison between LEACH, PSO, and the PSOGA. In all cases, the PSOGA showed significant improvement over LEACH for all the metrics. The PSOGA also showed improvements over PSO, albeit to a much lesser extent than the improvements compared to LEACH. ### BS at the Edge

To complete the study and evaluate the efficacy of the proposed algorithm, the BS was placed at the edge of the network, as shown in Figure 10a. This case study enabled the evaluation of the performance of the PSOGA when the location of the base station is at the edge of a 2 \(\times\) 4, 100 nodes configuration. In this case study, the PSOGA also showed notable improvements in various performance metrics. Figure 10b depicts the significant improvement in the number of packets sent to the BS, with the PSOGA exhibiting 278.94% and 9.0% improvements compared to LEACH and PSO, respectively. As shown in Figure 10c, PSOGA achieved improvements in the number of alive nodes by 192.93% and 12.47% as compared to LEACH and PSO, respectively. Furthermore, Figure 10d demonstrates the enhancements of 281.4% and 611.85% in the residual energy for PSOGA compared to LEACH and PSO, respectively. Similarly, substantial enhancements in the PDR by 302.96% and 66.28% for the PSOGA compared to LEACH and PSO, respectively, are visualized in Figure 10e. Additionally, Figure 10f depicts the improvements of 45.87% and 6.54% in the throughput of the network with the PSOGA compared to LEACH and PSO, respectively. The plotted curves are the averages of the data from 10 simulations. Figure 9: Overall lifetimes of sensor nodes, comparing the first node dead (FND), half node dead (HND), and last node dead (LND) between the proposed and existing models. ## 7 Conclusions and Future Scope

In this study, a trust-based PSOGA model was developed to increase the network lifetime in an IoT-based WSN environment.