A COMPREHENSIVE REVIEW OF ENERGY-EFFICIENT ALGORITHMS FOR WIRELESS SENSOR NETWORKS (WSNS) - ADVANCES IN CLUSTER-BASED AND OPTIMIZATION TECHNIQUES

DOI: https://doie.org/10.0113/Jbse.2025939097

Swapana Y., Dr. Kamalraj T., Dr. Balakrishna R.

Keywords:

Wireless Sensor Networks (WSNs), Energy-Efficient Algorithms, Cluster Head (CH) Selection, Optimization Techniques, Hybrid and AI-Driven Approaches.

Abstract:

Wireless Sensor Networks (WSNs) are vital to environmental monitoring, healthcare, and industrial automation. Despite their broad applicability, WSNs face persistent challenges, such as limited energy resources, delays in data transmission, unreliable packet delivery, and reduced network lifespan. These issues demand innovative solutions to optimize performance while conserving energy. This review examines advanced methodologies that address these challenges, focusing on Cluster Head (CH) selection, improved routing strategies, and optimization techniques like Cuckoo Search, Harmony Search, K-Nearest Neighbors (KNN), and Ant Colony Optimization (ACO). By analyzing these approaches, we highlight how they enhance network efficiency, improve packet delivery rates, and extend network lifetime. This study offers a detailed comparative analysis, outlining the advantages and limitations of both traditional and advanced algorithms. In addition, it identifies existing gaps in research, such as the need for adaptive and dynamic algorithms and better integration with AI technologies. Finally, this review explores emerging trends, including hybrid optimization techniques and AI-driven approaches, offering a roadmap for future advancements in WSNs. This synthesis aims to guide researchers and practitioners in developing next-generation solutions for more efficient and sustainable WSNs.

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