Hybrid Swarm Intelligence Approach for Energy Efficient Clustering and Routing in Wireless Sensor Networks

The aim of wireless sensor networks (WSNs) is to gather and transmit data from the environment to the base station. However, this can lead to excessive energy consumption, which can reduce the network's lifespan. To mitigate this issue, clustering is a popular technique that can enable energy-efficient data transmission. This study proposes a novel hybrid technique called the “Hybrid Artificial Bee Colony Algorithm and Particle Swarm Optimization (HABCPSO)” to enhance the cluster head selection in the LEACH algorithm. By incorporating PSO, the hybrid algorithm improves the global search behavior of the ABC and achieves an optimal cluster head location. This synergistic approach results in a 40% increase in residual battery power and maintains over 50% alive nodes even in later network rounds, outperforming ABC, PSO, and C-LEACH by substantial margins. Experimental results demonstrate the remarkable energy efficiency of HABCPSO. It selects an average of 48 cluster heads in initial rounds, compared to 65 for ABC, 68 for PSO, and 115 for C-LEACH. This optimized cluster configuration contributes to a notable reduction in energy consumption and a prolonged network lifetime.