Fuzzy-Logic-Based Clustering Approach for Wireless Sensor Networks Using Energy Predication

In order to collect information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Clustering provides an effective way to prolong the lifetime of WSNs. Current clustering approaches often use two methods: selecting cluster heads with more residual energy, and rotating...

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Bibliographic Details
Published inIEEE sensors journal Vol. 12; no. 9; pp. 2891 - 2897
Main Authors Lee, Jin-Shyan, Cheng, Wei-Liang
Format Journal Article
LanguageEnglish
Published IEEE 01.09.2012
Subjects
Base stations
Cluster head selection
Clustering algorithms
Energy consumption
energy predication
fuzzy reasoning
Input variables
Pragmatics
Steady-state
Wireless sensor networks
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Summary:In order to collect information more efficiently, wireless sensor networks (WSNs) are partitioned into clusters. Clustering provides an effective way to prolong the lifetime of WSNs. Current clustering approaches often use two methods: selecting cluster heads with more residual energy, and rotating cluster heads periodically, to distribute the energy consumption among nodes in each cluster and extend the network lifetime. However, most of the previous algorithms have not considered the expected residual energy, which is the predicated remaining energy for being selected as a cluster head and running a round. In this paper, a fuzzy-logic-based clustering approach with an extension to the energy predication has been proposed to prolong the lifetime of WSNs by evenly distributing the workload. The simulation results show that the proposed approach is more efficient than other distributed algorithms. It is believed that the technique presented in this paper could be further applied to large-scale wireless sensor networks.
ISSN:1530-437X
1558-1748
DOI:10.1109/JSEN.2012.2204737