Improved Soft-k-Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks

• Published in: IEEE internet of things journal Vol. 8; no. 6; pp. 4868 - 4881
• Main Authors: Zhu, Botao, Bedeer, Ebrahim, Nguyen, Ha H., Barton, Robert, Henry, Jerome
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 15.03.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation algorithms; Clustering; Clustering algorithms; Clustering by fast search and find of density peaks (CFSFDPs); Death; Density; Energy consumption; energy load balancing; kernel density estimation (KDE); Logic gates; multicluster heads (multi-CHs); Nodes; Probability; Routing; soft <italic xmlns:ali="http://www.niso.org/schemas/ali/1.0/" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">k -means; Wireless networks; Wireless sensor networks; wireless sensor networks (WSNs)

Energy load balancing is an essential issue in designing wireless sensor networks (WSNs). Clustering techniques are utilized as energy-efficient methods to balance the network energy and prolong its lifetime. In this article, we propose an improved soft-<inline-formula> <tex-math notation=&...