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Energy-Efficient Cluster Head Selection Scheme Based on Multiple Criteria Decision Making for Wireless Sensor Networks

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Abstract

Energy efficiency is an essential issue in the applications of wireless sensor networks (WSNs) all along. Clustering with data aggregation is a significant direction to improve energy efficiency through software. The selection of cluster head (CH) is the key issue in the clustering algorithm, which is also a multiple criteria decision making (MCDM) procedure. In this paper, a novel fuzzy multiple criteria decision making approach, which is based on trapezoidal fuzzy AHP and hierarchical fuzzy integral (FAHP), is introduced to optimize the selection of cluster heads to develop a distributed energy-efficient clustering algorithm. Energy status, QoS impact and location are taken into account simultaneously as the main factors that can influence the selection of cluster heads while each factor contains some sub-criteria. Fuzzy multiple attribute decision making is adopted to select optimal cluster heads by taking all factors into account synthetically. According to these criteria, each node computes a composite value by using fuzzy Integral. Then this composite value is mapped onto the time axis, and a time-trigger mechanism makes the node broadcast cluster head information. The rule that “first declaration wins” is adopted to form the cluster. Simulation results denote that our proposed scheme has longer lifetime and more eximious expansibility than other algorithms.

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Authors and Affiliations

  1. Research Center for Micro System Technology, Dalian University of Technology, 116024, Dalian, China

    Teng Gao, Ren Cheng Jin, Tai Bing Xu & Li Ding Wang

  2. School of Information Engineering, Dalian Ocean University, 116023, Dalian, China

    Jin Yan Song

Authors
  1. Teng Gao
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  2. Ren Cheng Jin
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  3. Jin Yan Song
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  4. Tai Bing Xu
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  5. Li Ding Wang
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Correspondence to Ren Cheng Jin.

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Gao, T., Jin, R.C., Song, J.Y. et al. Energy-Efficient Cluster Head Selection Scheme Based on Multiple Criteria Decision Making for Wireless Sensor Networks. Wireless Pers Commun 63, 871–894 (2012). https://doi.org/10.1007/s11277-010-0172-8

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  • DOI: https://doi.org/10.1007/s11277-010-0172-8

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