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Analytical network process based optimum cluster head selection in wireless sensor network

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Listed:
  • Haleem Farman
  • Huma Javed
  • Bilal Jan
  • Jamil Ahmad
  • Shaukat Ali
  • Falak Naz Khalil
  • Murad Khan

Abstract

Wireless Sensor Networks (WSNs) are becoming ubiquitous in everyday life due to their applications in weather forecasting, surveillance, implantable sensors for health monitoring and other plethora of applications. WSN is equipped with hundreds and thousands of small sensor nodes. As the size of a sensor node decreases, critical issues such as limited energy, computation time and limited memory become even more highlighted. In such a case, network lifetime mainly depends on efficient use of available resources. Organizing nearby nodes into clusters make it convenient to efficiently manage each cluster as well as the overall network. In this paper, we extend our previous work of grid-based hybrid network deployment approach, in which merge and split technique has been proposed to construct network topology. Constructing topology through our proposed technique, in this paper we have used analytical network process (ANP) model for cluster head selection in WSN. Five distinct parameters: distance from nodes (DistNode), residual energy level (REL), distance from centroid (DistCent), number of times the node has been selected as cluster head (TCH) and merged node (MN) are considered for CH selection. The problem of CH selection based on these parameters is tackled as a multi criteria decision system, for which ANP method is used for optimum cluster head selection. Main contribution of this work is to check the applicability of ANP model for cluster head selection in WSN. In addition, sensitivity analysis is carried out to check the stability of alternatives (available candidate nodes) and their ranking for different scenarios. The simulation results show that the proposed method outperforms existing energy efficient clustering protocols in terms of optimum CH selection and minimizing CH reselection process that results in extending overall network lifetime. This paper analyzes that ANP method used for CH selection with better understanding of the dependencies of different components involved in the evaluation process.

Suggested Citation

  • Haleem Farman & Huma Javed & Bilal Jan & Jamil Ahmad & Shaukat Ali & Falak Naz Khalil & Murad Khan, 2017. "Analytical network process based optimum cluster head selection in wireless sensor network," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-28, July.
    • Handle: RePEc:plo:pone00:0180848
    DOI: 10.1371/journal.pone.0180848
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    References listed on IDEAS

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    1. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    2. Shah Nazir & Sajid Anwar & Sher Afzal Khan & Sara Shahzad & Muhammad Ali & Rohul Amin & Muhammad Nawaz & Pavlos Lazaridis & John Cosmas, 2014. "Software Component Selection Based on Quality Criteria Using the Analytic Network Process," Abstract and Applied Analysis, Hindawi, vol. 2014, pages 1-12, December.
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    2. Taniegra Sussie Tarrega, 2019. "Web-based multi-criteria decision support system in screening and selection of priority projects for inclusion in agency’s annual budget proposal," Journal of Advances in Technology and Engineering Research, A/Professor Akbar A. Khatibi, vol. 5(1), pages 01-17.
    3. Rui Ding & Zehua Liu, 2024. "An IT2FS-ANP- and IT2FS-CM-Based Approach for Conducting Safety Risk Assessments of Nuclear Power Plant Building Projects," Mathematics, MDPI, vol. 12(7), pages 1-21, March.
    4. Jing Zhang & Shi-jian Liu & Pei-Wei Tsai & Fu-min Zou & Xiao-rong Ji, 2018. "Directional virtual backbone based data aggregation scheme for Wireless Visual Sensor Networks," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-27, May.

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