An energy-aware clustering algorithm for wireless sensor networks: GA-based approach
by Payal Khurana Batra; Krishna Kant
International Journal of Autonomous and Adaptive Communications Systems (IJAACS), Vol. 11, No. 3, 2018

Abstract: Energy conservation is the predominant requirement of wireless sensor networks. Clustering is a technique which helps in achieving the goal of energy efficiency and scalability. Several clustering approaches using genetic algorithm (GA) as an optimisation tool are proposed in the literature. Most of these clustering approaches lead to multi-objective optimisation. In this paper, we propose a GA-based clustering algorithm (GACA) which considers major factors responsible for effective clustering. The proposed approach has been compared with existing approaches for the best fit and optimal fit case. Simulation results show that the proposed GACA approach is more energy efficient than existing approaches and optimal fit results are better than the best fit results.

Online publication date: Wed, 01-Aug-2018

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