Energy-Distance-Function-Based Improved K-Means for Clustering Routing Algorithm

In wireless sensor networks (WSNs), conventional clustering routing algorithms often lead to uneven distribution of cluster heads (CHs), resulting in imbalanced and high-energy consumption. Addressing these challenges, this study introduces a novel algorithm, termed the energy distance function-base...

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Veröffentlicht in:	IEEE internet of things journal Jg. 11; H. 22; S. 36763 - 36774
Hauptverfasser:	Zhou, Lin, Zhang, Meng, Wei, Qian, Jin, Yong, Wang, Saidi, Yan, Jiayuan
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 15.11.2024 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	Adaptation models Adaptive algorithms Algorithms Cluster analysis Cluster head (CH) selection Clustering Clustering algorithms Distance factor Energy consumption energy distance function Energy distribution Energy efficiency Internet of Things K-means clustering Nodes Residual energy Routing Vector quantization wireless sensor network (WSN) Wireless sensor networks
ISSN:	2327-4662, 2327-4662
Online-Zugang:	Volltext
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