## 4 Comparative Analysis and Results
Then, the node with higher residual energy is elected as the chain head of a group. The transmission of data to a group chain head in every group over a chain is implemented in the fourth step. Finally, the obtained data are dispatched to a base station using a leader-to-leader transmission method. This method provides low energy dispersion and clustering overhead can occur. The other method used is LEACH-C (Low-Energy Adaptive Clustering Hierarchy Centralized), an individual-hop data transmission structure where cluster heads give the combined information to a base station, along with nodes' endurance level. The head node is the one whose endurance is above the threshold for the ongoing round, and the data are circulated throughout the entire arrangement. The matching of circulated identity to the core identity is interpreted for a lifetime of rounds. This protocol is mainly useful for short distances. The dissipation of endurance usage among available hubs is provided by LEACH-C, but this method is not easily upgraded or updated. Therefore, all procedures executing WSNs are compared with the proposed work to evaluate the average of the residual energy determined by the score of rounds. The average of the residual energy levels determined by the score rounds is calculated by various methods and classified in Table 2.  
The various methods for routing protocols and machine learning algorithms are analyzed and the outcomes are tabulated. From Table 1, the average residual energy by the number of rounds by Optimal-CBR is 0.99 per 0 rounds, 0.98 per 200 rounds, 0.95 \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline
**Various Methods and** & **0** & **200** & **400** & **600** & **800** & **1000** & **1200** \\ \hline Proposed & 1 & 0.99 & 0.96 & 0.92 & 0.84 & 0.76 & 0.72 \\ \hline LEACH-C & 0.91 & 0.84 & 0.82 & 0.73 & 0.7 & 0.6 & 0.59 \\ \hline Optimal-CBR & 0.99 & 0.98 & 0.95 & 0.8 & 0.75 & 0.7 & 0.65 \\ \hline CHIRON & 0.93 & 0.89 & 0.86 & 0.75 & 0.72 & 0.65 & 0.6 \\ \hline k-means & 0.95 & 0.92 & 0.94 & 0.79 & 0.73 & 0.69 & 0.64 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Differentiation of the average of residual energy along with the score of rounds in various methods. per 400 rounds, 0.8 per 600 round, 0.75 per 800 rounds, 0.7 per 1000 rounds, and 0.65 per 1200 rounds. K-means produced 0.95 per 1, 0.92 per 200, 0.94 per 400, 0.79 per 600, 0.73 per 800, 0.69 per 1000, and 0.64 per 1200. The CHIRON method yields 0.93 per 0, 0.89 per 200, 0.86 per 400, 0.75 per 600, 0.72 per 800, 0.65 per 1000, and 0.6 per 1200. LEACH-C gives 0.91 per 0, 0.84 per 200, 0.82 per 400, 0.73 per 600, 0.7 per 800, 0.6 per 1000, and 0.59 per 1200. Among these methods, our proposed method has higher average residual energy by the number of rounds than the other methods, and the values of the proposed method are 1 per 0, 0.99 per 200, 0.96 per 400, 0.92 per 600, 0.84 per 800, 0.76 per 1000, and 0.72 per 1200. Therefore, our proposed system scored high compared to the other methods. The node with a transmission latency higher than the threshold value in the WSN is called a dead node. The presence of a dead node indicates the reliability of the WSN. The comparative analysis of the first dead node for validation is shown in Figure 3. The measured value is greater for the proposed model than for the other values. This is due to the threshold configured in the models. It also depends on the user-defined data presented in the node. The first dead node was found after 500 rounds, showing that the proposed model has nodes with better reliability. The  
Figure 3: Comparative analysis of the first dead node for validation by the number of rounds in various methods. \begin{table}
\begin{tabular}{c c} \hline \hline
**Various Protocol Methods** & **First Dead Node for Validation** \\ \hline Proposed & 590 \\ \hline LEACH-C & 286 \\ \hline Optimal-CBR & 578 \\ \hline CHIRON & 332 \\ \hline k-means & 459 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Differentiation of first dead node for validation in several methods.