Clustering Routing Scheme Based on Quantum Beluga Whale Optimization Algorithm for Wireless Sensor Networks

Abstract

The low-powered design of routing protocols has become a vital concern in wireless sensor networks. For solving the difficulty in network load and energy consumption for the existing clustering method, we propose a novel clustering routing scheme. The quantum beluga whale optimization (QBWO) algorithm is designed to efficiently and centrally configure clusters, including cluster centroids, cluster members, cluster energy, cluster priority, and cluster validity period. It can not only transfer the computing energy consumption originally belonging to the node to base station, but also coordinate operation for the subsequent switching stage and steady stage. Simulation experiments show the superiority of QBWO. In comparison with existing clustering method, our work can achieve more balanced network load and energy consumption, demonstrating excellent energy efficiency and network lifetime.