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

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=&...

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Vydáno v:	IEEE internet of things journal Ročník 8; číslo 6; s. 4868 - 4881
Hlavní autoři:	Zhu, Botao, Bedeer, Ebrahim, Nguyen, Ha H., Barton, Robert, Henry, Jerome
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 15.03.2021 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	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)
ISSN:	2327-4662, 2327-4662
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Abstract	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="LaTeX">k </tex-math></inline-formula>-means (IS-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means) clustering algorithm to balance the energy consumption of nodes in WSNs. First, we use the idea of clustering by fast search and find of density peaks (CFSFDPs) and kernel density estimation (KDE) to improve the selection of the initial cluster centers of the soft <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means clustering algorithm. Then, we utilize the flexibility of the soft-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means and reassign member nodes considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, the concept of multicluster heads is employed to balance the energy consumption within clusters. Extensive simulation results under different network scenarios demonstrate that for small-scale WSNs with single-hop transmission, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death on average when compared to various clustering algorithms from the literature.
AbstractList	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="LaTeX">k </tex-math></inline-formula>-means (IS-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means) clustering algorithm to balance the energy consumption of nodes in WSNs. First, we use the idea of clustering by fast search and find of density peaks (CFSFDPs) and kernel density estimation (KDE) to improve the selection of the initial cluster centers of the soft <inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means clustering algorithm. Then, we utilize the flexibility of the soft-<inline-formula> <tex-math notation="LaTeX">k </tex-math></inline-formula>-means and reassign member nodes considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, the concept of multicluster heads is employed to balance the energy consumption within clusters. Extensive simulation results under different network scenarios demonstrate that for small-scale WSNs with single-hop transmission, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death on average when compared to various clustering algorithms from the literature. 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-[Formula Omitted]-means (IS-[Formula Omitted]-means) clustering algorithm to balance the energy consumption of nodes in WSNs. First, we use the idea of clustering by fast search and find of density peaks (CFSFDPs) and kernel density estimation (KDE) to improve the selection of the initial cluster centers of the soft [Formula Omitted]-means clustering algorithm. Then, we utilize the flexibility of the soft-[Formula Omitted]-means and reassign member nodes considering their membership probabilities at the boundary of clusters to balance the number of nodes per cluster. Furthermore, the concept of multicluster heads is employed to balance the energy consumption within clusters. Extensive simulation results under different network scenarios demonstrate that for small-scale WSNs with single-hop transmission, the proposed algorithm can postpone the first node death, the half of nodes death, and the last node death on average when compared to various clustering algorithms from the literature.
Author	Bedeer, Ebrahim Nguyen, Ha H. Zhu, Botao Barton, Robert Henry, Jerome
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SubjectTerms	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)
Title	Improved Soft-k-Means Clustering Algorithm for Balancing Energy Consumption in Wireless Sensor Networks
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