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A Novel Fuzzy Based Hybrid PSOGSA Algorithm in WSNs

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Published:19 February 2020Publication History

ABSTRACT

Lifetime and energy consumption are the main objectives of wireless sensor networks (WSNs). The existing methodologies have certain inhibitions which limit their applications. Clustering optimization is a major technique in any wireless sensor networks to optimize energy efficiency. Clustering technique assembles the objects of comparable shape in one shape. This technique is the excellent data assembly model for WSN, and it handles the redundant data within the network. The selection of the cluster head is an important feature in the clustering technique, then cluster heads cumulative the data and transmits to sink. Here fuzzy logic control algorithm has been proposed with hybridized particle swarm optimization algorithm and gravitational search algorithm to select cluster heads in WSN (FHPSOGSA). The algorithm is used to merge the constraints like remaining energy, node degree and distance to sink and select the best appropriate nodes as Cluster Head (CH). Simulation outcome displays that the proposed algorithm (FHPSOGSA) is establish to yield best results over other conventional algorithms.

References

  1. Akyildiz, I.F. Su, W. Sankarasubramaniam, Y.Cayirei, "Wireless sensor network: a survey," Computer Network, vol-38, pp. 393--422, 2002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Heinzelman, W.B., Chandrakasan, A.P., Balakrishnan, H., "An applicationspecific protocol architecture for wireless microsensor networks", in Proc. IEEE Trans. Wirel. Commun. pp. 660--670, 2002.Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Kim, J., Park, S., Han, Y., Chung, T., "CHEF: Cluster head election mechanism using fuzzy logic in wireless sensor networks", 10th International Conference on Advanced Communication Technology, pp. 654-- 659, 2008.Google ScholarGoogle ScholarCross RefCross Ref
  4. Bagci H, Yazici A.,"An energy aware Fuzzy approach to unequal clustering in wireless sensor network," in Proc. Appl. Soft Computing 13: 1741--1749. 2013.Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Cheng WL, Lee JS, "Fuzzy logic based clustering approach for wireless sensor networks using energy prediction," in Proc. IEEESensor Journal, pp. 2891--2897, 2012.Google ScholarGoogle Scholar
  6. Nayak, P., Devulapalli, A., "A fuzzy logic-based clustering algorithm for WSN to extend the network lifetime," in Proc. IEEE Sens. J, pp. 137--144. 2016.Google ScholarGoogle Scholar
  7. Yahya Kord Tamandani, Mahammad Ubaidullah Bakhari, "SEPFL, routing protocol based fuzzy logic control to extend the lifetime and throughput of the wireless sensor network," in Proc. Journal Wireless network, pp. 647--653. 2016.Google ScholarGoogle Scholar
  8. Pawan Singh Mehra, Mohammad Najmud Doja, Bashir Alam, "Fuzzy based enhanced cluster head selection (FBECS) for WSN," in Proc. Journal of Saud University, 2018.Google ScholarGoogle Scholar
  9. C. Sun, J. Zeng, J. Pan, S. Xue, and Y. Jin, "A new fitness estimation strategy for particle swarm optimization", in Proc. Information Sciences, vol. 221, pp. 355--370, 2013.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. E. Rashedi, H. Nezamabadi-pour and S. Saryazdi, "GSA: a gravitational search algorithm", in Proc. Information Sciences, Vol. 179, pp. 2232--2248, 2009.Google ScholarGoogle ScholarDigital LibraryDigital Library

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  • Published in

    cover image ACM Other conferences
    ICDCN '20: Proceedings of the 21st International Conference on Distributed Computing and Networking
    January 2020
    460 pages
    ISBN:9781450377515
    DOI:10.1145/3369740

    Copyright © 2020 ACM

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    New York, NY, United States

    Publication History

    • Published: 19 February 2020

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