## 4 Experimental Validation  
This section examines the performance of the HMSFO-EARS model under a varying number of nodes. The proposed model is simulated using the MATLAB tool. A detailed comparative result analysis took place with recent models such as  
* Node status and score-based route optimization protocol (NSSROP) [12]: involves DSR and OLSR with the novel scoring mechanism for path selection;
* Power-Efficient Gathering in Sensor Information Systems (PEGASIS) Routing Protocol (PRRP) [13]: a chain cluster-based routing protocol;
* Proposed directional transmission-based energy aware routing protocol (PDORP) [14]: integrates PEGASIS and DSR for route selection;
* Dynamic source routing (DSR) [15]: forms a route on-demand when a transmitting node requests one;
* Low energy adaptive clustering hierarchy (LEACH): a classical clustering scheme. Table 2 offers the parameter settings involved in the simulation process. Table 3 and Figure 3 report a comparative average energy consumption (AECN) analysis of the HMSFO-EARS model with recent models. The outcomes specified that the LEACH model has shown poor performance with higher AECN values. Then, the PDORP and DSR models have indicated moderately closer and reduced AECN values. \begin{table}
\begin{tabular}{l l} \hline \hline
**Parameter** & **Value** \\ \hline Number of nodes & 50–250 \\ \hline Traffic type & CBR \\ \hline Simulation time & 100 s \\ \hline Network size & 250 \(\times\) 250 m\({}^{2}\) \\ \hline Packet size & 4000 bits \\ \hline MAC protocol & IEEE 802.15.4 \\ \hline Transmission range & 30 m \\ \hline Sensing range & 10 m \\ \hline Location of BS & 125 \(\times\) 125 m\({}^{2}\) \\ \hline Node distribution & Random \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Parameter Settings. Though the PRRP model has reached reasonable AECN values, the HMSFO-EARS model has obtained the least AECN values under all nodes. For example, with 50 nodes, the HMSFO-EARS model has presented the least AECN of 5.21 J whereas the NSSROP, PRRP, PDORP, DSR, and LEACH models have attained an increased AECN of 6.10 J, 9.71 J, 8 J, 9.37 J, and 9.37 J, respectively. A comparative number of alive nodes (NAN) study of the HMSFO-EARS model is portrayed in Table 4 and Figure 4. The results inferred the betterment of the HMSFO-EARS model with increasing values of NAN. For instance, in Round 1, the HMSFO-EARS model has revealed a higher NAN of 99% whereas the NSSROP, PRRP, PDORP, DSR, and LEACH methods have portrayed a lower NAN of 98%, 97%, 98%, 96%, and 96%, respectively. In addition, in Round 5, the HMSFO-EARS method has portrayed a higher NAN of 70% while the NSSROP, PRRP, PDORP, DSR, and LEACH models have shown the lowest NAN of 66%, 45%, 40%, 26%, and 32%, correspondingly. \begin{table}
\begin{tabular}{l l l l l l l} \hline \multicolumn{6}{l}{**Average Energy Consumption (J)**} \\ \hline
**No. of Nodes** & **HMSFO-EARS** & **NSSROP** & **PRRP** & **PDORP** & **DSR** & **LEACH** \\ \hline
50 & 5.21 & 6.10 & 9.71 & 8.00 & 9.37 & 9.37 \\ \hline
100 & 5.48 & 6.10 & 6.10 & 7.39 & 16.45 & 16.45 \\ \hline
200 & 5.28 & 6.57 & 5.55 & 7.46 & 9.71 & 24.21 \\ \hline
250 & 5.35 & 6.51 & 5.62 & 7.87 & 10.73 & 27.75 \\ \hline \end{tabular}
\end{table} 
Table 3: AECN analysis of HMSFO-EARS system with existing approaches under different nodes. Figure 3: AECN analysis of HMSFO-EARS system under different nodes. A comparative throughput (THRO) study of the HMSFO-EARS method is demonstrated in Table 5 and Figure 5 under different pause times. The pause time refers to a period of time during which a node temporarily stops transmitting or processing data. This is often used as a means of power management, as transmission and processing activities consume a significant amount of energy in WSN. The outcomes show the betterment of the HMSFO-EARS approach with increasing values of THRO.