Clustering routing algorithm for WSN based on BBO optimized K-means

doi:10.7523/j.ucas.2022.065

Abstract

Abstract: Aimed at the problems of limited energy and short network lifetime in wireless sensor network,BBOK-GA based on biogeographic algorithm optimization K-means was proposed.In the clustering stage, biogeographic algorithm optimization K-means was firstly used to prevent K-means from falling into the local optimum. According to the energy factor and distance factor, a new fitness function was designed to select optimal cluster heads and complete the clustering. And genetic algorithm was used to search the optimal routing path towards base station for cluster heads. The simulation results indicate that BBOK-GA reduces the network energy consumption，increases the network throughput and extends the network life time compared to LEACH, LEACH-C, and K-GA.

Key words: wireless sensor network, biogeography-based optimization, genetic algorithm, K-means algorithm, clustering-based routing

CLC Number:

TN393

PENG Cheng, TAN Chong, LIU Hong, ZHENG Min. Clustering routing algorithm for WSN based on BBO optimized K-means[J]. Journal of University of Chinese Academy of Sciences, 2024, 41(3): 357-364.

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