Efficient transmission based on genetic evolutionary algorithm

Jin Fan and Kit Guan Lim and Helen Sin Ee Chuo and Min Keng Tan and Ali Farzamnia and Kenneth Tze Kin Teo (2022) Efficient transmission based on genetic evolutionary algorithm.

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Abstract

Today’s society has grappled with the age of big data. Widespread use of informatization technology has promoted the development of artificial intelligence and communication technologies, which can play an important role in communication networks. In this paper, an energy-saving mechanism based on genetic algorithm in wireless sensor network (WSN) is proposed. The basic working principle and main characteristics of genetic algorithm (GA) are summarized, and the theory, technology and existing problems of GA are discussed. Through the analysis of the transmission efficiency of GA, a new genetic evolutionary algorithm combined with the characteristics of ant colony algorithm (ACO) is proposed. Through the simulation of the transmission performance of genetic optimization algorithm, the comparison of transmission energy consumption between GA and evolutionary algorithm is analyzed, and the evolutionary algorithm with higher transmission performance is obtained. Results showed that the proposed hybrid genetic algorithm with ant colony optimization (GACO) delivers 78.70% and 73.51% lower number of transmission failures than GA and ACO respectively.

Item Type:	Proceedings
Keyword:	Genetic Algorithm, Evolutionary Algorithms, Transmission Efficiency
Subjects:	Q Science > QA Mathematics > QA1-939 Mathematics Q Science > QA Mathematics > QA1-939 Mathematics > QA299.6-433 Analysis
Department:	FACULTY > Faculty of Engineering
Depositing User:	ABDULLAH BIN SABUDIN -
Date Deposited:	04 Nov 2024 09:27
Last Modified:	04 Nov 2024 09:27
URI:	https://eprints.ums.edu.my/id/eprint/41727

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