Aug 2026· Engineering Research Express· Vol 8· 0 citations· 41 references
Physics
TL;DR
A distributed K-means clustering algorithm integrated with a modified low energy adaptive clustering hierarchy-improved energy distance protocol for clustering and CH selection achieves improved network lifetime, energy balancing, and scalability while maintaining competitive throughput performance compared with existing protocols.
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.
Wireless Sensor Networks (WSNs) use resource-constrained sensor nodes to continuously monitor ambient conditions and serve as data sinks for various Internet of Things (IoT) applications. However, maximizing Energy Efficiency (EE) while maintaining reliable data delivery remains a significant challenge. Existing cluste...
P. Kumbhar, A. Naik· International Journal of Ele...· 0 citations
The core research goal of this paper is to optimize dynamic routing protocols to improve the performance of the classic LEACH protocol in heterogeneous WSNs through a real-time adaptive scheme, which relies on two core methods: a cluster head selection mechanism based on the residual energy criterion, and a priority ho...
V. Barbudhe, Shruti Dixit· International journal of com...· 0 citations
The results indicate that E2CMR improves energy efficiency, network stability, and routing performance and is applicable for large-scale energy-constrained WSNs.
S. Priyadarshini, A. T.· International journal of com...· 0 citations
A cluster-based proactive routing protocol designed for three-tier energy-heterogeneous WSNs, aiming to enhance network lifetime and energy efficiency, and modified to address the challenge of long transmission distances for low-power nodes by strategically deploying them in specific network zones.
F. A. Mohamed, E. Hassan, M. Dessouky et al.· Scientific Reports· 0 citations
ThGCDTR-RP is proposed, an energy-efficient clustering and routing protocol that integrates Grey Wolf Optimizer, Cheetah Optimizer, and Differential Evolution for cluster-head (CH) selection that consistently outperforms LEACH, LPSO, LGWO, WOA-P, and LACO.
Xuan Yang, Jia-Qi Yan, De-Sheng Wang et al.· Journal of King Saud Univers...· 0 citations
The obtained results validate that the proposed hybrid ALEOA-IGGO framework effectively addresses the critical challenges of energy-aware clustering and reliable routing in large-scale and dynamic WSN environments.
D. Faridha Banu, N. Kumaresan· Scientific Reports· 0 citations
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