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Efficient cluster head selection using Naïve Bayes classifier for wireless sensor networks

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Abstract

Data mining and approaches based on it have always been of approaches that have been considered in solving problems in the field of computer, but on some issues, this approach has been neglected. The area of wireless sensor networks and specifically the issue of optimal determining of the cluster head node are of these issues. To solve the problem of optimal determining of the cluster head node, Naïve Bayes that is the subset of data mining techniques is used in this paper. The results obtained after simulation of the presented algorithm show that the efficiency of this algorithm is significantly higher compared with other approaches that have so far been used to solve this problem, and thus it can be said that using this algorithm will lead to improved outcomes of solving this problem.

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Authors and Affiliations

  1. Department of Computer Engineering, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

    Vahid Jafarizadeh & Amin Keshavarzi

  2. Department of Mathematics, Marvdasht Branch, Islamic Azad University, Marvdasht, Iran

    Tajedin Derikvand

Authors
  1. Vahid Jafarizadeh
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  2. Amin Keshavarzi
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  3. Tajedin Derikvand
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Correspondence to Amin Keshavarzi.

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Jafarizadeh, V., Keshavarzi, A. & Derikvand, T. Efficient cluster head selection using Naïve Bayes classifier for wireless sensor networks. Wireless Netw 23, 779–785 (2017). https://doi.org/10.1007/s11276-015-1169-8

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  • DOI: https://doi.org/10.1007/s11276-015-1169-8

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