TEJAS Journal of Technologies and Humanitarian Science

Methods based on several features of wireless sensor network clustering employing machine learning, optimization, and classical techniques: Review, taxonomy, discoveries from research, difficulties, and upcoming paths

Km Anjuman Bano
Computer Science and Engineering, Institute of Technology & Management, Aligarh, India

Author

Sushil Kumar Sharma
Computer Science and Engineering, Institute of Technology & Management, Aligarh, India

Author

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Abstract:

Wireless Sensor Networks (WSNs) are pivotal in various applications ranging from environmental monitoring to smart cities. Clustering in WSNs is a crucial strategy for optimizing energy consumption, enhancing network longevity, and improving data aggregation efficiency. This paper presents a comprehensive review of clustering methods in WSNs, focusing on techniques incorporating machine learning, optimization, and classical approaches. We provide a detailed taxonomy of these methods, highlight significant research discoveries, discuss the challenges encountered, and propose potential future research directions.

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