Wireless Sensor Networks (WSNs) have emerged as a vital enabler for diverse Internet of Things (IoT) applications, encompassing smart cities, healthcare monitoring, industrial automation, and environmental sensing. However, the inherent energy constraints of sensor nodes present a significant challenge, often resulting in limited network longevity, degraded performance, and inefficient data transmission. This paper introduces an advanced energy-efficient clustering protocol grounded in fuzzy logic, designed to address the limitations of conventional methods such as LEACH and HEED. Unlike traditional protocols that rely on probabilistic or static heuristics, the proposed framework employs a dynamic, multi-criteria fuzzy inference system to optimize the selection of Cluster Heads (CHs). Critical parameters including residual energy, node centrality, and proximity to the base station are evaluated to ensure robust CH selection, uniform energy dissipation, and enhanced scalability. Simulation results reveal marked improvements in network metrics—achieving a 40.8% reduction in overall energy consumption, a 51.2% increase in throughput, and a 55% enhancement in network lifespan compared to baseline methods. Additionally, the model significantly improves CH stability, minimizing control overhead and elevating network reliability. This study demonstrates the efficacy of integrating fuzzy logic into WSN clustering strategies, offering a highly adaptive, intelligent, and sustainable solution for next-generation IoT deployments.
Wireless Sensor Networks (WSNs), Internet of Things (IoT), Energy Efficiency, Fuzzy Logic, Cluster Head Selection, Clustering Techniques.
The authors confirm contribution to the paper as follows:
Conceptualization: Indhumathi R, Saloni Vaishnav, Anurag Shrivastava, Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal; Writing- Original Draft Preparation: Shrivastava, Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal; Visualization: Indhumathi R, Saloni Vaishnav and Anurag Shrivastava; Investigation: Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal; Supervision: Indhumathi R, Saloni Vaishnav and Anurag Shrivastava; Validation: Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal; Writing- Reviewing and Editing: Indhumathi R, Saloni Vaishnav, Anurag Shrivastava, Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal; All authors reviewed the results and approved the final version of the manuscript.
The author(s) received no financial support for the research, authorship, and/or publication of this article.
No funding was received to assist with the preparation of this manuscript.
The authors have no conflicts of interest to declare that are relevant to the content of this article.
Data sharing is not applicable to this article as no new data were created or analysed in this study.
All authors have equal contribution in the paper and all authors have read and agreed to the published version of the manuscript.
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Indhumathi R, Saloni Vaishnav, Anurag Shrivastava, Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal, “Energy Efficient Wireless Sensor Networks: A Fuzzy Logic Approach for IoT Optimization”, Journal of Machine and Computing, vol.5, no.4, pp. 2254-2268, October 2025, doi: 10.53759/7669/jmc202505175.
© 2025 Indhumathi R, Saloni Vaishnav, Anurag Shrivastava, Vishwanil Suman, Montater Muhsn Hasan and Saloni Bansal. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
