A distributed K-means-based improved energy distance LEACH routing protocol for wireless sensor networks

Abstract

Wireless sensor networks (WSNs) are increasingly prominent due to their applicability across diverse domains. WSNs represent the future of intelligent sensing, offering robust, flexible, and monitoring solutions to support the proliferation of the Internet of Things (IoT), in applications such as smart cities, autonomous systems, digital twins, bio-integrated sensing, and large-scale climate monitoring. Although numerous clustering-based routing protocols have been proposed, achieving energy-efficient clustering and cluster head (CH) selection remains a significant challenge. Additionally, most of the approaches are either non-adaptive or centralized. Addressing these challenges, this paper proposes a distributed K-means clustering algorithm integrated with a modified low energy adaptive clustering hierarchy-improved energy distance (DK-means-LEACH-IED) protocol for clustering and CH selection. The proposed method starts with a timer-based selection of initial centroid nodes, then applies K-means clustering to those nodes. CHs are then selected using an adaptive, weighted energy-distance function that accounts for nodes’ residual energy and their distance from the cluster centroid. The proposed protocol is implemented in OMNET++ using the Castalia framework, followed by a comprehensive performance evaluation and comparison with LEACH and the centralized Energy-driven K-means-based LEACH routing protocols. The results demonstrate that DK-means-LEACH-IED achieves improved network lifetime, energy balancing, and scalability while maintaining competitive throughput performance compared with existing protocols. The proposed protocol improves network stability during the critical depletion phase by extending the 70% node survival lifetime by up to 14.04% and achieves throughput improvement of up to 49.18% compared with the evaluated benchmark protocols, demonstrating its ability to balance energy utilization and communication efficiency for emerging IoT applications.