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Recent Advances in Computer Science and Communications

Editor-in-Chief

ISSN (Print): 2666-2558
ISSN (Online): 2666-2566

Research Article

An Energy Efficient Routing Approach to Enhance Coverage for Application- Specific Wireless Sensor Networks Using Genetic Algorithm

Author(s): Amandeep K. Sohal*, Ajay K. Sharma and Neetu Sood

Volume 14, Issue 4, 2021

Published on: 10 December, 2019

Page: [1086 - 1096] Pages: 11

DOI: 10.2174/2666255813666191210144821

Price: $65

Abstract

Background: An information gathering is a typical and important task in agriculture monitoring and military surveillance. In these applications, minimization of energy consumption and maximization of network lifetime have prime importance for green computing. As wireless sensor networks comprise of a large number of sensors with limited battery power and deployed at remote geographical locations for monitoring physical events, therefore it is imperative to have minimum consumption of energy during network coverage. The WSNs help in accurate monitoring of remote environment by collecting data intelligently from the individual sensors.

Objective: The paper is motivated from green computing aspect of wireless sensor network and an Energy-efficient Weight-based Coverage Enhancing protocol using Genetic Algorithm (WCEGA) is presented. The WCEGA is designed to achieve continuously monitoring of remote areas for a longer time with least power consumption.

Methods: The cluster-based algorithm consists two phases: cluster formation and data transmission. In cluster formation, selection of cluster heads and cluster members areas based on energy and coverage efficient parameters. The governing parameters are residual energy, overlapping degree, node density and neighbor’s degree. The data transmission between CHs and sink is based on well-known evolution search algorithm i.e. Genetic Algorithm.

Results: The results of WCEGA are compared with other established protocols and shows significant improvement of full coverage and lifetime approximately 40% and 45% respectively.

Conclusion: This paper proposes an evolutionary method to improve an energy-efficient clustering protocol for longer full coverage.

Keywords: Clustering, wireless sensor networks, energy-efficient, green computing, full coverage, WCEP.

Graphical Abstract

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