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A Comparative Study on Prominent Strategies of Cluster Head Selection in Wireless Sensor Networks

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Integrated Intelligent Computing, Communication and Security

Part of the book series: Studies in Computational Intelligence ((SCI,volume 771))

Abstract

Wireless sensor networks (WSNs) have an imprint in every aspect of human life from very small to large-scale application. On one hand, energy-constrained sensor nodes are expected to run for a long duration. On the other hand, designing and maintaining sustainable WSNs is a very major issue nowadays. It may be very costly either to replace expired batteries or even impossible in hostile environments. So, there is a necessity to conserve the energy of the nodes so as to extend the network lifetime. After a deep review of the literature, we found that network lifetime can be extended by dividing it into groups (clusters). Decisions regarding all the operations in all groups are made by respective cluster heads (CHs). But selecting the best CHs is a critical issue to be resolved so as to utilize energy consumption most efficiently. This study can be a recommendation for researchers while optimally selecting WSN CHs.

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References

  1. Akyildiz, I.F., W. Su, Y. Sankarasubramaniam, and E. Cayirci. 2002. Wireless sensor networks: A survey. Computer Networks 38 (4): 393–422.

    Article  Google Scholar 

  2. Anastasi, Giuseppe, et al. 2009. Energy conservation in wireless sensor networks: A survey. Ad hoc networks 7 (3): 537–568.

    Article  Google Scholar 

  3. Rault, Tifenn, Abdelmadjid Bouabdallah, and Yacine Challal. 2014. Energy efficiency in wireless sensor networks: A top-down survey. Computer Networks 67: 104–122.

    Article  Google Scholar 

  4. Afsar, M. Mehdi, and H. Mohammad, N. Tayarani. 2014. Clustering in sensor networks: A literature survey. Journal of Network and Computer Applications 46: 198–226.

    Article  Google Scholar 

  5. Heinzelman,W.R., A. Chandrakasan, and H. Balakrishnan. (2000, January). Energy-efficient communication protocol for wireless microsensor networks. In Proceedings of the 33rd annual Hawaii international conference on system sciences, 2000, 10-pp. IEEE.

    Google Scholar 

  6. Abbasi, A.A., and M. Younis. 2007. A survey on clustering algorithms for wireless sensor networks. Computer Communications 30 (14): 2826–2841.

    Article  Google Scholar 

  7. Logambigai, R., and Arputharaj Kannan. 2016. Fuzzy logic based unequal clustering for wireless sensor networks. Wireless Networks 22 (3): 945–957.

    Article  Google Scholar 

  8. Gherbi, Chirihane, et al. 2017. A survey on clustering routing protocols in wireless sensor networks. Sensor Review 37 (1): 12–25.

    Article  Google Scholar 

  9. Younis, O., and S. Fahmy. 2004. HEED: A hybrid, energy-efficient, distributed clustering approach for ad hoc sensor networks. IEEE Transactions on Mobile Computing 3 (4): 366–379.

    Article  Google Scholar 

  10. Qing, L., Q. Zhu, and M. Wang. 2006. Design of a distributed energy-efficient clustering algorithm for heterogeneous wireless sensor networks. Computer Communications 29 (12): 2230–2237.

    Article  Google Scholar 

  11. Mao, S., C. Zhao, Z. Zhou, and Y. Ye. 2013. An improved fuzzy unequal clustering algorithm for wireless sensor network. Mobile Networks and Applications 18 (2): 206–214.

    Article  Google Scholar 

  12. Bagci, H., and A. Yazici. 2013. An energy aware fuzzy approach to unequal clustering in wireless sensor networks. Applied Soft Computing 13 (4): 1741–1749.

    Article  Google Scholar 

  13. Sert, S.A., H. Bagci, and A. Yazici. 2015. MOFCA: Multi-objective fuzzy clustering algorithm for wireless sensor networks. Applied Soft Computing 30: 151–165.

    Article  Google Scholar 

  14. Gajjar, S., M. Sarkar, and K. Dasgupta. 2016. FAMACROW: Fuzzy and ant colony optimization based combined mac, routing, and unequal clustering cross-layer protocol for wireless sensor networks. Applied Soft Computing 43: 235–247.

    Article  Google Scholar 

  15. Kim, J.M., S.H. Park, Y.J. Han, and T.M. Chung. (2008, February). CHEF: Cluster head election mechanism using fuzzy logic in wireless sensor networks. In ICACT 2008. 10th international conference on Advanced communication technology, vol. 1, 654–659. IEEE.

    Google Scholar 

  16. Yuan, H.Y., S.Q. Yang, and Y.Q. Yi. (2011, May). An energy-efficient unequal clustering method for wireless sensor networks. In 2011 international conference on computer and management (CAMAN), 1–4. IEEE.

    Google Scholar 

  17. Chen, G., C. Li, M. Ye, and J. Wu. 2009. An unequal cluster-based routing protocol in wireless sensor networks. Wireless Networks 15 (2): 193–207.

    Article  Google Scholar 

  18. Zhao, X., and N. Wang. (2010, May). An unequal layered clustering approach for large scale wireless sensor networks. In 2010 2nd international conference on future computer and communication (ICFCC), vol. 1, V1-750. IEEE.

    Google Scholar 

  19. Gupta, I., D. Riordan, and S. Sampalli. (2005, May). Cluster-head election using fuzzy logic for wireless sensor networks. In Communication networks and services research conference, 2005. Proceedings of the 3rd annual, 255–260. IEEE.

    Google Scholar 

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Correspondence to Priti Maratha .

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Maratha, P., Kapil (2019). A Comparative Study on Prominent Strategies of Cluster Head Selection in Wireless Sensor Networks. In: Krishna, A., Srikantaiah, K., Naveena, C. (eds) Integrated Intelligent Computing, Communication and Security. Studies in Computational Intelligence, vol 771. Springer, Singapore. https://doi.org/10.1007/978-981-10-8797-4_39

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