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Spectral Partitioning and Fuzzy C-Means Based Clustering Algorithm for Wireless Sensor Networks

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Wireless Algorithms, Systems, and Applications (WASA 2017)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10251))

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Abstract

In wireless sensor networks (WSNs), sensor nodes are usually powered by battery and thus have very limited energy. Saving energy is an important goal in designing a WSN. It is known that clustering is an effective method to prolong network lifetime. However, how to cluster sensor nodes cooperatively and achieve an optimal number of clusters in a WSN still remains an open issue. In this paper, we first propose an analytical model to determine the optimal number of clusters in a wireless sensor network. We then propose a centralized cluster algorithm based on the spectral partitioning method. The advantage of the method is that the partitioned subgraphs have an approximately equal number of vertices while minimizing the number of edges between the two subgraphs. Then, we present a distributed clustering algorithm based on fuzzy C-means method and the selection strategy of cooperative nodes and cluster heads based on fuzzy logic. Finally, simulation results show that the proposed algorithms outperform the hybrid energy-efficient distributed clustering algorithm in terms of energy cost and network lifetime.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (Nos. 61503309, 61373179, 61373178, 61402381), Natural Science Key Foundation of Chongqing (cstc2015jcyjBX0094), Natural Science Foundation of Chongqing (CSTC2016JCYJA0449).

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Authors and Affiliations

  1. College of Electronic and Information Engineering, Southwest University, Chongqing, 400715, China

    Jianji Hu & Songtao Guo

  2. School of Chemistry and Chemical Engineering, Southwest University, Chongqing, 400715, China

    Defang Liu

  3. Department of Electrical and Computer Engineering, Stony Brook University, Stony Brook, NY, 11794, USA

    Yuanyuan Yang

Authors
  1. Jianji Hu
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  2. Songtao Guo
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  3. Defang Liu
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  4. Yuanyuan Yang
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Corresponding author

Correspondence to Songtao Guo .

Editor information

Editors and Affiliations

  1. Texas Christian University, Fort Worth, Texas, USA

    Liran Ma

  2. New Jersey Institute of Technology, Newark, New Jersey, USA

    Abdallah Khreishah

  3. University of Oslo, Oslo, Norway

    Yan Zhang

  4. University of North Georgia, Dahlonega, Georgia, USA

    Mingyuan Yan

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Hu, J., Guo, S., Liu, D., Yang, Y. (2017). Spectral Partitioning and Fuzzy C-Means Based Clustering Algorithm for Wireless Sensor Networks. In: Ma, L., Khreishah, A., Zhang, Y., Yan, M. (eds) Wireless Algorithms, Systems, and Applications. WASA 2017. Lecture Notes in Computer Science(), vol 10251. Springer, Cham. https://doi.org/10.1007/978-3-319-60033-8_15

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  • DOI: https://doi.org/10.1007/978-3-319-60033-8_15

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60032-1

  • Online ISBN: 978-3-319-60033-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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