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An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic

Received: 7 October 2014    Accepted: 11 October 2014    Published: 27 October 2014
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Abstract

Wireless sensor network (WSN) is composed of a large number of sensor nodes that are connected to each other. In order to collect more efficient information, wireless sensor networks are classified into groups. Classification is an efficient way to increase the lifetime of wireless sensor networks. In this network, devices have limited power processing and memory. Due to limited resources in wireless sensor networks, increasing lifetime was always of attention. An efficient routing method is called clustering based routing that finds optimum cluster heads and finding the correct number of them in each cluster remains a challenge. In this paper, we propose a novel and efficient method for clustering using fuzzy logic with four appropriate inputs and combine it with the good features of Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results show that our method is more efficient compared to other distributed algorithms, because the proposed method if fully distributed. The result show that compared to centralized, the speed is more and its energy consumption is less.

Published in International Journal of Intelligent Information Systems (Volume 3, Issue 6-1)

This article belongs to the Special Issue Research and Practices in Information Systems and Technologies in Developing Countries

DOI 10.11648/j.ijiis.s.2014030601.17
Page(s) 38-44
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 Networks, Clustering, Cluster Head, Fuzzy Logic, Lifetime

References
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[2] J. N. Al-Karak and A. E.Kamal, “Routing techniques in wireless sensor network: A survey,” IEEE wireless communications, Vol. 11, pp. 6-28, 2004.
[3] I. F. Akyildiz, W. Su, Y. Sankarasubramaniam, and E. Cayirci, “Wireless sensor networks: a survey,” Computer Networks, Vol. 38, pp. 393- 422, 2002.
[4] J. Breckling, Ed., The Analysis of Directional Time Series: Applications to Wind Speed and Direction, ser. Lecture Notes in Statistics. Berlin, Germany: Springer, vol. 61, 1989.
[5] Seyyed Jalaleddin Dastgheib, Hamed Oulia, Mohammad Reza Sadeqi Ghassami, An Efficient Approach for Clustering in Wireless Sensor Network Using Fuzzy Logic, International Conference on Computer Science and Network Technology, Harbin, China 24-26, IEEE, 2011
[6] I. Gupta, D. Riordan and S. Sampalli, “Cluster-head Election using Fuzzy Logic for Wireless Sensor Networks,” In Proceedings of the 3rd Annual Communication Networks and Services Research Conference, Washington, DC, USA, pp.255-260, 2005.
[7] J. Myoung 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),Gangwon-Do,South_Korea, pp.654-659, 2008.
[8] D. De, A Distributed Algorithm for Localization Error Detection-Correction, Use in In-network Faulty Reading Detection:Applicability in Long-Thin Wireless Sensor Networks, in Conference IEEE 2009.
[9] Heinzelman, A. Chandrakasan and H. Balakrishnan, An application-specific protocol architecture for wireless microsensor networks, in IEEE Transactions on Wireless communications, pp. 660 - 670, 2002.
[10] G. W. Nurcahyo, Selection of Defuzzification Method to Obtain Crisp Value for Representing Uncertain Data in a Modified Sweep Algorithm, Journal of Computer Science & Technology (JCS&T), Vol. 3 No. 2, October 2003.
[11] F. Vanheel, J. Verhaevert, "Automated Linear Regression Tools Improve RSSI WSN Localization in Multipath Indoor Environment," EURASIP Journal on Wireless Communications and Networking, vol.2011/2011,pp.1-27, 2011.
[12] http://www.mathworks.com/FuzzyLogic Toolbox user’s guide.
[13] Z. Qin, M. Bai and D. Ralescu, A fuzzy control system with application to production planning problems, Information Sciences Elsevier Volume 181, Issue 5, Pages 1018-1027, 2011
[14] G. C. D. Sousa and B. K. Bose. “A FUZZY Set Theory Based Control of a Phase-Controlled Converter DC Machine Drive”, 1991 IEEE hi.App. Sot. Annu. Meeting, pp.854-861, 1991.
[15] D. Z. Šaletić, D. Velašević: The formal description of a rule based fuzzy expert system, Proceedings of Symposium on Computer Scences and Information Technologies, Kopaonik 27-31. III 2000, pp. 251 –220, YUiNFO 2000
[16] W. Van Leekwijck, E.E. Kerre:Defuzzification: criteria and cla sification, Fuzzy Sets and Systems, 108, pp. 159-178,1999
[17] Dragan Z. Saletic, Dusan M. Velasevic, Nikos E. Mastorakis, "Analysis of Basic Defuzzification Techniques" inRecent Advances in Computers, Computing and Communications , pp. 247-252, WSEAS Press, 2002.
[18] E. H. Mamdani, "Application of fuzzy logic to approximate reasoning using linguistic synthesis," IEEE Transactions on Computers, Vols. C-26, pp. 1182-1191, 1977.
Cite This Article
  • APA Style

    Morteza Asghari Reykandeh, Ismaeil Asghari Reykandeh. (2014). An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic. International Journal of Intelligent Information Systems, 3(6-1), 38-44. https://doi.org/10.11648/j.ijiis.s.2014030601.17

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    ACS Style

    Morteza Asghari Reykandeh; Ismaeil Asghari Reykandeh. An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic. Int. J. Intell. Inf. Syst. 2014, 3(6-1), 38-44. doi: 10.11648/j.ijiis.s.2014030601.17

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    AMA Style

    Morteza Asghari Reykandeh, Ismaeil Asghari Reykandeh. An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic. Int J Intell Inf Syst. 2014;3(6-1):38-44. doi: 10.11648/j.ijiis.s.2014030601.17

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  • @article{10.11648/j.ijiis.s.2014030601.17,
      author = {Morteza Asghari Reykandeh and Ismaeil Asghari Reykandeh},
      title = {An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic},
      journal = {International Journal of Intelligent Information Systems},
      volume = {3},
      number = {6-1},
      pages = {38-44},
      doi = {10.11648/j.ijiis.s.2014030601.17},
      url = {https://doi.org/10.11648/j.ijiis.s.2014030601.17},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijiis.s.2014030601.17},
      abstract = {Wireless sensor network (WSN) is composed of a large number of sensor nodes that are connected to each other. In order to collect more efficient information, wireless sensor networks are classified into groups. Classification is an efficient way to increase the lifetime of wireless sensor networks. In this network, devices have limited power processing and memory. Due to limited resources in wireless sensor networks, increasing lifetime was always of attention. An efficient routing method is called clustering based routing that finds optimum cluster heads and finding the correct number of them in each cluster remains a challenge. In this paper, we propose a novel and efficient method for clustering using fuzzy logic with four appropriate inputs and combine it with the good features of Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results show that our method is more efficient compared to other distributed algorithms, because the proposed method if fully distributed. The result show that compared to centralized, the speed is more and its energy consumption is less.},
     year = {2014}
    }
    

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  • TY  - JOUR
    T1  - An Efficient Approach Toward Increasing Wireless Sensor Networks Lifetime Using Novel Clustering in Fuzzy Logic
    AU  - Morteza Asghari Reykandeh
    AU  - Ismaeil Asghari Reykandeh
    Y1  - 2014/10/27
    PY  - 2014
    N1  - https://doi.org/10.11648/j.ijiis.s.2014030601.17
    DO  - 10.11648/j.ijiis.s.2014030601.17
    T2  - International Journal of Intelligent Information Systems
    JF  - International Journal of Intelligent Information Systems
    JO  - International Journal of Intelligent Information Systems
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    PB  - Science Publishing Group
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    UR  - https://doi.org/10.11648/j.ijiis.s.2014030601.17
    AB  - Wireless sensor network (WSN) is composed of a large number of sensor nodes that are connected to each other. In order to collect more efficient information, wireless sensor networks are classified into groups. Classification is an efficient way to increase the lifetime of wireless sensor networks. In this network, devices have limited power processing and memory. Due to limited resources in wireless sensor networks, increasing lifetime was always of attention. An efficient routing method is called clustering based routing that finds optimum cluster heads and finding the correct number of them in each cluster remains a challenge. In this paper, we propose a novel and efficient method for clustering using fuzzy logic with four appropriate inputs and combine it with the good features of Low-Energy Adaptive Clustering Hierarchy (LEACH). Simulation results show that our method is more efficient compared to other distributed algorithms, because the proposed method if fully distributed. The result show that compared to centralized, the speed is more and its energy consumption is less.
    VL  - 3
    IS  - 6-1
    ER  - 

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Author Information
  • Department of Computer Engineering, Islamic Azad University Khoy Branch, Khoy, Iran

  • Department of Computer Engineering, Islamic Azad University Sari Branch, Sari, Iran

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