Maximizing the Lifetime of Wireless Sensor Networks: Integrating K-Means Clustering with LEACH Protocol to Improve Energy Efficiency
Noman Ashraf, Rungrat Viratikul, Teerapol Silawan, Chaiyachet Saivichit · 2024
In addressing the critical challenge of energy conservation within Wireless Sensor Networks (WSNs), this study introduces a novel approach that synergizes K-Means clustering with the LEACH (Low Energy Adaptive Clustering Hierarchy) protocol to enhance network longevity significantly. By refining the Cluster Head (CH) selection process through the integration of the K-Means algorithm, this research not only prioritizes nodes with higher residual energy but also considers their geographical proximity, thereby ensuring a more balanced energy consumption across the network. This methodical approach to clustering diverges from LEACH's conventional random selection, proposing a strategic framework that effectively minimizes energy wastage and optimizes communication pathways. Empirical validation, conducted through MATLAB simulations, unequivocally demonstrates that this integrated protocol markedly outperforms the standard LEACH protocol in terms of energy efficiency, thereby substantially prolonging the operational lifespan of WSNs. The findings of this study hold substantial implications for the deployment of WSNs in various applications, from environmental monitoring to healthcare, where maximizing network lifetime without compromising functionality is paramount. This research contributes to the existing literature by presenting a viable solution to one of the most pressing issues in WSN deployment and sets a new benchmark for future studies in this domain.