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A Fuzzy Logic based Unequal Clustering Protocol for Heterogeneous Wireless Sensor Networks
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 179 - Number 28 |
| Year of Publication: 2018 |
| Authors: Priya Bhatnagar, Subhash Chandra |
10.5120/ijca2018916624
|
Priya Bhatnagar, Subhash Chandra . A Fuzzy Logic based Unequal Clustering Protocol for Heterogeneous Wireless Sensor Networks. International Journal of Computer Applications. 179, 28 ( Mar 2018), 16-20. DOI=10.5120/ijca2018916624
Abstract
Wireless Sensor Networks (WSNs) have gained due importance for applications requiring remote sensing. The major challenges faced are related to energy and routing. The sensor nodes being battery operated devices of limited resources, techniques like data aggregation, selective node activation and energy efficient routing are adopted with main focus of saving energy. The objective is to prolong life of the network and also distribute the load evenly among the nodes. Several approaches have been suggested in literature; mostly for homogeneous WSNs only. Fuzzy logic has recently been opted for selection of cluster heads in these networks. This paper proposes a fuzzy logic based unequal clustering protocols for WSNs in heterogeneous settings. Four decision criteria for selecting cluster heads are input to the fuzzy logic which gives two outputs instead of one. This unique feature makes the proposed method effective.
References
- W. Dargie and C. Poellabauer, “Fundamentals of wireless sensor networks: theory and practice”, John Wiley and Sons. pp. 168–183, 2010.
- S. Tarannum, “Energy Conservation Challenges in Wireless Sensor Networks: A Comprehensive Study”, Wireless Sensor Network, Vol. 2, pp. 483-491, 2010.
- W. R. Heinzelman, A. Chandrakasan, H. Balakrishnan, “Energy-Efficient Communication Protocol for Wireless Microsensor Networks”, Proceedings of the 33rd Annual Hawaii International Conference on System Sciences, pp. 10–19, 2000.
- O. Younis and S. Fahmy, “HEED: A hybrid, energy-efficient, distributed clustering approach for ad-hoc sensor networks”, IEEE Transactions on Mobile Computing., Vol. 3, pp. 366–379, 2004.
- M. Ye, C .F. Li, G. H. Chen and J. Wu, “EECS: an energy efficient clustering scheme in wireless sensor networks”, Proceedings of the 24th IEEE International Performance, Computing, and Communication Conference (IPCCC 2005), pp. 535–540, 2005.
- C. F. Li, M. Ye, G. H. Chen and J. Wu, “An energy-efficient unequal clustering mechanism for wireless sensor network”, Proceedings of the IEEE International Conference on Mobile Adhoc and Sensor Systems Conference, pp. 596–640, 2005.
- H. Li, Y. Liu, W. Chen, W. Jia, B. Li, J. Xiong, “COCA: Constructing Optimal clustering architecture to maximize sensor network lifetime”, Computers Communications, Vol. 36, pp. 256-268, 2013.
- Y. Liao, H. Qi, W. Li, Load-balanced clustering algorithm with distributed self organization for wireless sensor networks, IEEE Sensors Journal, vol. 13, no. 5, pp. 1498-1506, 2013.
- Z. Xu, Y. Yin and J. Wang, “An Density-based Energy-efficient Routing Algorithm in Wireless Sensor Networks Using Game Theory,” International Journal of Future Generation Communication and Networking, vol. 5, pp. 99-112, 2012.
- W. A. Ellatief, O. Younes, H. Ahmed and M. Hadhoud, “Energy Efficient Density-based Clustering Technique for Wireless Sensor Network”, Proceedings of the 8th International Conference on Knowledge and Smart Technology (KST), 2016.
- I. Gupta, D. Riordan and S. Sampalli, “Cluster-head election using fuzzy logic for wireless sensor networks”, Proceedings of the Communication Networks and Services Research Conference, pp. 255–260, 2005.
- J. Kim, S. Park, Y. Han and T. Chung, “CHEF: cluster head election mechanism using fuzzy logic in wireless sensor networks”, Proceedings of the 10th International Conference on Advanced Communication Technology, pp. 654–659, 2008.
- H. Bagci and A.Yazici “An Energy Aware Fuzzy Unequal Clustering Algorithm for Wireless Sensor Networks,” Proceedings of IEEE Conference on Fuzzy Systems, pp. 1-8, 2010.
- B. Baranidharan and B. Santhi, “DUCF: Distributed load balancing Unequal Clustering in wireless sensor networks using Fuzzy approach”, Applied Soft Computing, Vol. 40, pp. 495–506, 2016.
- E. H. Mamdani, “Application of fuzzy logic to approximate reasoning using linguistic synthesis”, IEEE Transactions on Computers, vol. 26, no. 12, pp. 1182–1191, 1977.
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