## 5 Results and Discussion
### Performance Evaluation  
Figure 5a shows the initial network topology when nodes were generated, whereas Figure 5b shows the network topologies after CH selection for the evaluated protocols. The network topology results show the transmission path and distance. As shown in Equation 14, since the transmission distance was related to the transmission energy, the energy consumption could be estimated from the network topology result. LEACH-C retrieved an unsuitable CHs distribution compared to the other protocols that used swarm intelligence. In fact, LEACH-C provided long distances for some node-CH transmission paths. The other protocols retrieved a relatively similar energy consumption at the nodes. The red lines in Figure 5b allowed for the estimation of the CH transmission energy, which mainly depended on the distance. SSMOECHS provided similar consumption compared to the other protocols, but with a more evenly distributed transmission energy. Therefore, SSMOECHS could properly distribute the energy consumption of the entire network to increase energy efficiency. Figures 6 and 7 show the simulation results under the homogeneous setup, in which the initial energy of all nodes in the WSN was 1 J. SSMOECHS had the latest first node dead compared to the other protocols, thus providing a more stable network for a longer period. Given that both half and last node dead withstand the longest, SSMOECHS also extended the network lifetime. In Figure 6, the last node dead of SSMOECHS occurred last, indicating the improved network lifetime. Figure 7 shows the total energy consumption per protocol. Again, SSMOECHS outperformed the other protocols by providing the most efficient energy consumption. The execution rounds at which first, half, and last node dead occurred under the homogeneous setup are listed in Table 4. \begin{table}
\begin{tabular}{c c} \hline \hline
**Parameter** & **Value** \\ \hline Swarm size & 40 \\ Maximum number of iterations (\(C_{\text{max}}\)) & 100 \\ Maximum number of groups & 4 \\ Global leader limit & 10 \\ Local leader limit & 20 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Swarm parameters for optimization. Figure 5: Network topology results according to protocol. (**a**) Initial network topology and (**b**) results for every evaluated protocol. (Black lines, transmission node–CH; red lines, transmission CH–CH or CH–BS). Figure 6: Alive nodes according to protocol execution round under homogeneous setup. Figures 8 and 9 show the simulation results under the heterogeneous setup, in which each node started with different energy levels between 0.5 and 1 J. Figure 8 shows that SSMOECHS retrieved the latest first, half, and last node dead. Comparing Figures 6 and 8, it can be seen that the performance of SSMOECHS and SMOTECP was similar, but it was notably higher than PSO-C. After PSO-C determined the expected CH position, the nearest node was found, which seemed to undermine energy efficiency more notably under the heterogeneous than under the homogeneous setup. Figure 9 confirmed that SSMOECHS consumes energy more efficiently than the other protocols under the heterogeneous setup. The execution rounded at which first, half, and last node dead occurred under the heterogeneous setup are listed in Table 5.  
Table 6 lists the network stable period, unstable period, and lifetime, where stability corresponds to all the sensor nodes being alive. Under the homogeneous setup, SSMOECHS improved the stability period by 20%, 12.9%, and 7.4% compared to LEACH-C, PSO-C, and SMOTECP, respectively. Likewise, the network lifetime was improved by 12.3%, 5.6%, and 3.5%. Under the heterogeneous setup, SSMOECHS improved the stability period by 60%, 41.6%, and 2.2% compared to LEACH-C, PSO-C, and SMOTECP, respectively. Moreover, the network lifetime was improved by 2.6%, 2.2%, and 0.7%, respectively. Overall, the results confirm that SSMOECHS improved both network stability and lifetime compared to other CH selection methods.