Genetic Algorithm based Chain Leader Election in Wireless Sensor Network for Precision Farming

Hamzarul Alif Hamzah and Norah Tuah and Lim, Kit Guan and Tan, Min Keng and Ismail Saad and Tze, Kenneth,Kin Teo (2020) Genetic Algorithm based Chain Leader Election in Wireless Sensor Network for Precision Farming. In: IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology, 26-27 Sep 2020, Kota Kinabalu, Malaysia.

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Official URL: https://ieeexplore.ieee.org/document/9257835

Abstract

Wireless Sensor Network (WSN) is one of the commonly used technologies in Precision Farming (PF). It provides farmers with accurate real-time information on their farms. In practice, WSN consists of numerous wireless sensor nodes, where each node relies on limited energy sources such as battery to maintain its operation. The energy management issue in WSN has gained attention of scholars, leading to new protocols or schemes developed over the years. Conventionally, PEGASIS protocol selects chain leader without considering the distance and residual energy level of each sensor node. As such, it might increase the energy consumption rate to transmit collected data from sensor node to sink. Inadequate energy management leads to rapid energy drain and eventually shorten the lifespan of WSN. Therefore, this study aims to prolong the lifespan of WSN while minimizing the energy consumption. Genetic Algorithm (GA) is proposed to enhance the chain leader selection scheme of the conventional PEGASIS. The proposed GA will select optimum chain leader by considering the energy consumption rate of each node. As such, the proposed algorithm is able to increase node's transmission as well as improve the lifespan of WSN by 50% as compared to the conventional approach.

Item Type:	Conference or Workshop Item (Paper)
Keyword:	Genetic algorithm , Wireless sensor network , Precision farming
Subjects:	T Technology > TJ Mechanical engineering and machinery
Department:	FACULTY > Faculty of Engineering
Depositing User:	NORAINI LABUK -
Date Deposited:	29 Jul 2021 08:34
Last Modified:	29 Jul 2021 09:23
URI:	https://eprints.ums.edu.my/id/eprint/29918

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