Title: An energy-aware clustering algorithm for wireless sensor networks: GA-based approach

Authors: Payal Khurana Batra; Krishna Kant

Addresses: Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India ' Department of Computer Science and Engineering, Jaypee Institute of Information Technology, Noida, India

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.

Keywords: clustering; network lifetime; energy efficiency; genetic algorithm; wireless sensor networks; WSNs.

DOI: 10.1504/IJAACS.2018.093696

International Journal of Autonomous and Adaptive Communications Systems, 2018 Vol.11 No.3, pp.275 - 292

Received: 01 Mar 2016
Accepted: 30 Jan 2017
Published online: 01 Aug 2018 *

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