Adaptive Hybrid HOA–PSO with Periodic Cluster Head Rotation for Energy-Efficient WSNs

Abstract

The appropriate choice of a Cluster Head (CH) is crucial towards improving the performance and extending the operating life of the wireless sensor networks (WSNs), which are required to work with a severe energy restriction. The proposed paper presents an Adaptive Hybrid HOA-PSO algorithm with Periodic Cluster Head Rotation (AHHCR), which integrates the global exploration nature of the HOA and the fast convergence nature of PSO. To guarantee a proper timing of the energy spending as well as even distribution of the loads across the network, a multi-objective cost function defined in terms of the residual energy, sink distance, and long-term data load is used.

Large-scale model experiments involving 300 rounds indicate that AHHCR is significantly superior to traditional clustering protocols, including LEACH, PSO, GWO, and HOA. The algorithm achieves a 48 percent improvement in the average number of active nodes in the last round over the second-best performer (GWO) and increases the network survivability by over sixfold over LEACH. On top of that, AHHCR ensures the total decrease in energy use between about 5% and 16% compared to other metaheuristic standards. Despite the fact that the hybridism of AHHCR slightly adds a computational burden, the increase in the execution time, which is 0.41 s in a MATLAB simulation framework, is insignificant and, thus, indicates the practicality of its implementation.

The strength and excellence of AHHCR is further supported by the statistical analysis using the ANOVA and Tukey-HSD tests. These findings confirm the appropriateness of the algorithm to dynamic WSN-based Internet of Things applications that require real-time, energy-efficient, and balanced CH selection.