## 3 Materials and Methods
### Hybrid K-Medoids with IABC-Based CH-Selection Algorithm
Figure 12: Comparison of Jitter. Figure 13: Buffer occupancy. #### 4.3.10 CH-Selection-Time Analysis

Figure 15 depicts the time performance of the CH-selection method. Compared to existing methods, the proposed CH selection results in a shorter execution time. The time will be extended if the number of CHs increases. Compared to the conventional algorithm, the introduced method achieves a faster execution time (37 s) in the first cluster head. #### 4.3.11 Energy Consumption vs. Cluster

Figure 16 depicts energy- consumption comparison for different clusters. The energy usages of CL-HHO provide minimum value compared to other conventional algorithms in different clusters. It achieves the minimum energy usage for different CH when compared to other algorithms. Figure 16: Energy consumption for Different Clusters. Figure 15: CH-selection time. #### 4.3.12. Hop Count

The average number of hops as the network grows is depicted in Figure 17. The quantity of intermediate nodes involved in the packet-relay process affects the number of hops. The results offer a more precise relationship between node count and average hop count. CL HHO exploits the SN that can send packets over great distances. In other words, a node with a more excellent transmission range can travel fewer hops to reach its destination. On the other hand, the number of hops required to relay transmitted packets increases for an existing algorithm. Implementing the HHO method when energy-hole situations arise enhances network restructuring. ## 5 Conclusions

The k-medoid with IABC and CL-HHO has been proposed for clustering and routing in WSN. The CL-HHO hybrid technique determines the RP with the lowest energy consumption. MATLAB is used to implement all of the work, and the results are compared to some existing techniques. Multiple nodes are used to calculate QoS-performance metrics. When comparing HEED, EECRP, GWO, CL-ALO, and the proposed CL-HHO, the latter works well. Finally, the proposed k-medoids-IABC technique combined with the CL-HHO algorithm will be a better alternative to power-based routing in WSN. As a result, more iteration may be required to select the most appropriate path. As a result, in the future, a better strategy should be proposed instead of distance estimation to improve the execution speed of the route search. In the future, a new CL routing protocol based on optimization could extend network lifetime and improve WSN performance. Compared to the HEED, EECRP, GWO, and CL-ALO, the introduced CL-HHO, increased network lifetime by 36.58%, 27.27%, 19.14%, and 9.80%, respectively. According to the experimental data, it outperforms HEED, EECRP, GWO, and CL-ALO in terms of QoS performance. Furthermore, adaptive hybrid optimization and deep learning will be proposed to investigate application-specific routing-data schemes to maximize overall routing network performance. Conceptualization, R.S. ; data curation, R.S. and G.M.A. ; formal analysis, S.P. and G.M.A. ; funding acquisition, G.M.A. ; investigation, X.X. ; project administration, S.P. and D.S. ; resources, X.X., O.I.K. and D.S. ; software, X.X. and D.S. ; validation, R.S., O.I.K. and S.P. ; visualization, S.P. ; writing--review and editing, O.I.K. All authors have read and agreed to the published version of the manuscript. Figure 17: Hop Count. **Funding:** This work is supported by the National Natural Science Foundation of China (No. 62172095), the Natural Science Foundation of Fujian Province (Nos. 2020)01875 and 2022J01644). **Data Availability Statement:** Not applicable. **Acknowledgments:** The authors thank the Natural Science Foundation of Fujian Province China. **Conflicts of Interest:** The authors declare no conflict of interest. ## References

* [PERSON] et al. (2021) [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON]; [PERSON] Wireless Sensor Network (WSN) Configuration Method to Increase Node Energy Efficiency through Clustering and Location Information. _Symmetry_**2021**, _13_, 390. [CrossRef]
* [PERSON] et al.