Energy-Aware LEACH: A Weighted Metric Approach for Dynamic Cluster Head Selection in WSN

Wireless Sensor Networks (WSNs) are critical in different applications, from environmental monitoring to industrial automation. Effectively managing energy within WSNs is crucial to extend network longevity and ensure continuous data collection. This study introduces an implementation of the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol, a widely adopted approach for energy-efficient clustering in WSNs. LEACH addresses energy imbalances among sensor nodes by dynamically selecting cluster heads in a distributed manner. In this implementation, we propose a novel cluster head selection technique that incorporates a weighted metric considering three key parameters: node energy level, energy gradient, and distance from the sink. The introduced metric aims to enhance the robustness and adaptability of the protocol in diverse network scenarios. Simulation results underscore the effectiveness of the proposed LEACH implementation in achieving energy-efficient clustering and extending the network’s operational lifespan. Experiments conducted using MATLAB R (2021b) software demonstrated that the proposed algorithm increased the network lifespan by 41.18% and resulted in a significant reduction in energy consumption by about 65.38%. This highlights that the suggested energy-saving clustering hierarchy algorithm has significantly improved the performance.