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Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks

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International Journal of Computer Applications
© 2015 by IJCA Journal
Volume 113 - Number 19
Year of Publication: 2015
Authors:
Gaurang Raval
Madhuri Bhavsar
10.5120/19938-2104

Gaurang Raval and Madhuri Bhavsar. Article: Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks. International Journal of Computer Applications 113(19):41-47, March 2015. Full text available. BibTeX

@article{key:article,
	author = {Gaurang Raval and Madhuri Bhavsar},
	title = {Article: Improving Energy Estimation based Clustering with Energy Threshold for Wireless Sensor Networks},
	journal = {International Journal of Computer Applications},
	year = {2015},
	volume = {113},
	number = {19},
	pages = {41-47},
	month = {March},
	note = {Full text available}
}

Abstract

In this paper an energy usage estimation technique (LCEFCM) has been proposed which employs the Fuzzy C-Means clustering for creating clusters in the Wireless Sensor Networks. LCEFCM reduces the energy consumption considerably compared to other clustering methods like simulated annealing and K-Means clustering. It applies the dynamic clustering mechanism combined with balanced clustering method. LCEFCM outperforms LEACHC, LEACHC Estimate(LCE) and LCEKMeans for various performance measuring factors like network lifetime, data received, alive nodes etc.

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