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An information entropy based-clustering algorithm for heterogeneous wireless sensor networks

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Abstract

This paper proposes a novel dynamic, distributive, and self-organizing entropy based clustering scheme that benefits from the local information of sensor nodes measured in terms of entropy and use that as criteria for cluster head election and cluster formation. It divides the WSN into two-levels of hierarchy and three-levels of energy heterogeneity of sensor nodes. The simulation results reveal that the proposed approach outperforms existing baseline algorithms in terms of energy consumption, stability period, and the network lifetime.

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Authors and Affiliations

  1. Department of Computer Science, Faculty of Computers and Informatics, University of Benha, Benha, Egypt

    Walid Osamy

  2. Department of Computer Science, College of Sciences, University of Sharjah, Sharjah, United Arab Emirates

    Ahmed M. Khedr

  3. Mathematics Department, Faculty of Science, Zagazig University, Zagazig, Egypt

    Ahmed Salim & Ahmed M. Khedr

  4. Qassim University, P.O. Box 931, Buridah, Kingdom of Saudi Arabia

    Walid Osamy & Ahmed Salim

Authors
  1. Walid Osamy
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  2. Ahmed Salim
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  3. Ahmed M. Khedr
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Correspondence to Walid Osamy.

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Osamy, W., Salim, A. & Khedr, A.M. An information entropy based-clustering algorithm for heterogeneous wireless sensor networks. Wireless Netw 26, 1869–1886 (2020). https://doi.org/10.1007/s11276-018-1877-y

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  • DOI: https://doi.org/10.1007/s11276-018-1877-y

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