A dhole optimization algorithm-based energy-efficient clustering method for prolonging the lifetime of heterogeneous WSNs

Abstract

This paper introduces DOA-EEC, energy-efficient clustering for heterogeneous WSN (HWSN), a metaheuristic optimization-based energy efficient clustering algorithm based on dhole optimization algorithm (DOA) for optimal CH selection. Specifically, the method enhances network longevity by utilizing these parameters in a smart way a residual energy, distance between nodes, number of neighboring nodes, multi-hop communication and average remaining energy of the entire network. All these factors place together lead to better CH selection and help also reduce the hot-spot problem, which is a critical issue in case of WSNs. Finally, DOA-EEC significantly outperforms recent optimization techniques with respect to stability period, residual energy, network lifetime, throughput and number of apt CHs through extensive simulations. The proposed algorithm is thoroughly evaluated against a variety of state-of-the-art methods, and statistical tests indicate a considerable performance advantage over the benchmark algorithms used in this work.