Journal of Electrical and Electronic Engineering

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Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection

Received: 25 November 2016    Accepted: 29 November 2016    Published: 08 December 2016
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Abstract

Lifetime enhancement has always been of crucial importance for energy constrained sensor network due to resource limitations of sensor nodes. The energy of sensor nodes is mostly utilized for data transmission to the base station. clustering which could increase the network life time indirectly; so, various algorithms have been proposed for clustering and cluster-head selection, and LEACH is one of the most important algorithms. In this article, we offer a new and effective design to cluster and select the best possible cluster-head and also to have the best energy consumption and as a result to increase the network life time, using fuzzy logic inference system. In our offered algorithm, applying some effective and basic parameters in fuzzy inference system, we have increased the network life time and also the mean energy consumption into the LEACH algorithm.

DOI 10.11648/j.jeee.s.2015030201.33
Published in Journal of Electrical and Electronic Engineering (Volume 3, Issue 2-1, March 2015)

This article belongs to the Special Issue Research and Practices in Electrical and Electronic Engineering in Developing Countries

Page(s) 111-115
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Wireless Sensor Network, Clustering, Fuzzy Logic, Life Time, LEACH Algorithm

References
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[2] J. Yick, B. Mukherjee, and D. Ghosal, "Wireless sensor network survey," Computer Networks, vol. 52, no.12, pp. 2292-2330, 2008.
[3] W. Heinzelman, A. Chandrakasan and H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks”, In proceedings of the 33rd Hawaii International Conference on System Sciences (HICSS '00), January 2007.
[4] J. Kim, S. Park, Y. Han and T. Chung, “CHEF: Cluster Head Election mechanism using Fuzzy logic in Wireless Sensor Networks”, 10th International Conference on Advanced Communication Technology, ICACT 2008. pp. 654 – 659, Feb 2008.
[5] Ran, H. Z., “Improving on LEACH Protocol of Wireless Sensor Networks Using Fuzzy Logic,” Journal of Information & Computational Science, vol. 7(3), pp. 767-775, 2010.
[6] W. Heinzelman, A. Chandrakasan, and H. Balakrishnan. “An application-specific protocol architecture for wireless microsensor networks”, in IEEE Transactions on Wireless Communications, 1(4), pp. 660-670, Oct 2008.
[7] Ameer Ahmed Abbasi, Mohamed F. Younis, "A survey on clustering algorithms for wireless sensor networks.," Computer Communications, Vols. 30(14-15):, pp. 2826-2841, 2009.
[8] Heinzelman, A. Chandrakasan and H. Balakrishnan, "An application-specific protocol architecture for wireless microsensor networks", in IEEE Transactions on Wireless communications, pp. 660 - 670, Oct 2009.
[9] Z. Qin, M. Bai and D. Ralescu, "A fuzzy control system with application to production planning problems", Information Sciences Elsevier Volume 181, Issue 5, PP 1018-1027, 1 March 2010.
[10] A. K. Singh، N. Purohit, K. P. Singh، M. Shukla, “A novel approach for lifetime analysis of sensor network using fuzzy logic” IEEE India Conference (INDICON), PP 568-574. Dec. 2011.
[11] T. Shu, M. Krunz, and S. Vrudhula, “Power balanced coverage-time optimization for clustered wireless sensor networks,” in Proceedingsof the 6th ACM international symposium on Mobile ad hoc networking and computing. ACM, PP 256-300 feb 2012.
[12] O. Younis, M. Krunz, and S. Ramasubramanian, “Node clustering in wireless sensor networks: Recent developments and deployment challenges,” IEEE Network, vol. 20, no. 3, pp. 20–25, M 2013.
[13] Nasrin Abazari Torghabeh, Mohammad Reza Akbarzadeh, Mohammad Hossein Yaghmaee, “Cluster Head Selection using a Two-Level Fuzzy Logic in Wireless Sensor Networks”, 2nd International conference on Computer Engineering and Technology (ICCET), pp. 357-361, M 2014.
[14] D. C. Hoang, R. Kumar, S. K. Panda, “Fuzzy C-Means Clustering Protocol for Wireless Sensor Networks”, IEEE International Symposium on Industrial Electronics (ISIE) pp. 3477-3482,2010.M. Young, The Technical Writer’s Handbook. Mill Valley, CA: University Science, 2014.
[15] Zohre Arabi, “HERF: A Hybrid Energy Efficient Routing using a Fuzzy Method in Wireless Sensor Networks”, International Conference on Intelligent and Advanced Systems (ICIAS), PP 896-901, Oct 2014.
[16] Chung-ming, Shau-yuan lu, Cheng ya teng, “Location Aware Sensor and Fuzzy Data Mule”, Proceedings of the Ninth International Conference on Machine Learning and Cybernetics, Qingdao, pp. 2535-2640, July 2014.
Author Information
  • Sama Technical and Vocational Training College, Islamic Azad University, Kermanshah Branch, Kermanshah, Iran

  • Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

  • Department of Electrical Engineering, Kermanshah Branch, Islamic Azad University, Kermanshah, Iran

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  • APA Style

    Ali Pirasteh, Mohammadsajad Ahmadi, Hosein Seyedi. (2016). Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection. Journal of Electrical and Electronic Engineering, 3(2-1), 111-115. https://doi.org/10.11648/j.jeee.s.2015030201.33

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    ACS Style

    Ali Pirasteh; Mohammadsajad Ahmadi; Hosein Seyedi. Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection. J. Electr. Electron. Eng. 2016, 3(2-1), 111-115. doi: 10.11648/j.jeee.s.2015030201.33

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    AMA Style

    Ali Pirasteh, Mohammadsajad Ahmadi, Hosein Seyedi. Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection. J Electr Electron Eng. 2016;3(2-1):111-115. doi: 10.11648/j.jeee.s.2015030201.33

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  • @article{10.11648/j.jeee.s.2015030201.33,
      author = {Ali Pirasteh and Mohammadsajad Ahmadi and Hosein Seyedi},
      title = {Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection},
      journal = {Journal of Electrical and Electronic Engineering},
      volume = {3},
      number = {2-1},
      pages = {111-115},
      doi = {10.11648/j.jeee.s.2015030201.33},
      url = {https://doi.org/10.11648/j.jeee.s.2015030201.33},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.jeee.s.2015030201.33},
      abstract = {Lifetime enhancement has always been of crucial importance for energy constrained sensor network due to resource limitations of sensor nodes. The energy of sensor nodes is mostly utilized for data transmission to the base station. clustering which could increase the network life time indirectly; so, various algorithms have been proposed for clustering and cluster-head selection, and LEACH is one of the most important algorithms. In this article, we offer a new and effective design to cluster and select the best possible cluster-head and also to have the best energy consumption and as a result to increase the network life time, using fuzzy logic inference system. In our offered algorithm, applying some effective and basic parameters in fuzzy inference system, we have increased the network life time and also the mean energy consumption into the LEACH algorithm.},
     year = {2016}
    }
    

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    T1  - Maximization Lifetime in Wireless Sensor Network by Fuzzy Logic for Cluster Head Selection
    AU  - Ali Pirasteh
    AU  - Mohammadsajad Ahmadi
    AU  - Hosein Seyedi
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    DO  - 10.11648/j.jeee.s.2015030201.33
    T2  - Journal of Electrical and Electronic Engineering
    JF  - Journal of Electrical and Electronic Engineering
    JO  - Journal of Electrical and Electronic Engineering
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    EP  - 115
    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.jeee.s.2015030201.33
    AB  - Lifetime enhancement has always been of crucial importance for energy constrained sensor network due to resource limitations of sensor nodes. The energy of sensor nodes is mostly utilized for data transmission to the base station. clustering which could increase the network life time indirectly; so, various algorithms have been proposed for clustering and cluster-head selection, and LEACH is one of the most important algorithms. In this article, we offer a new and effective design to cluster and select the best possible cluster-head and also to have the best energy consumption and as a result to increase the network life time, using fuzzy logic inference system. In our offered algorithm, applying some effective and basic parameters in fuzzy inference system, we have increased the network life time and also the mean energy consumption into the LEACH algorithm.
    VL  - 3
    IS  - 2-1
    ER  - 

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