欢迎访问中国科学院大学学报,今天是

中国科学院大学学报 ›› 2024, Vol. 41 ›› Issue (3): 357-364.DOI: 10.7523/j.ucas.2022.065

• 电子信息与计算机科学 • 上一篇    下一篇

基于BBO优化K-means算法的WSN分簇路由算法

彭程1,2, 谭冲2, 刘洪2, 郑敏2   

  1. 1. 中国科学院大学, 北京 100049;
    2. 中国科学院上海微系统与信息技术研究所, 上海 200050
  • 收稿日期:2021-12-31 修回日期:2022-06-21 发布日期:2022-06-27
  • 通讯作者: 彭程,E-mail:cheng.peng@mail.sim.ac.cn
  • 基金资助:
    国家重点研发计划(2020YFB2103300)资助

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

PENG Cheng1,2, TAN Chong2, LIU Hong2, ZHENG Min2   

  1. 1. University of Chinese Academy of Sciences, Beijing 100049, China;
    2. Shanghai Institute of Microsystem and Information Technology, Chinese Academy of Sciences, Shanghai 200050, China
  • Received:2021-12-31 Revised:2022-06-21 Published:2022-06-27

摘要: 针对无线传感器网络中传感器节点能量有限、网络生存期短的问题,提出一种基于生物地理学算法优化K-means的无线传感器网络分簇路由算法BBOK-GA。成簇阶段,通过生物地理学优化算法改进K-means算法,避免求解时陷入局部最优。根据能量因子和距离因子设计了新的适应度函数选举最优簇首,完成分簇任务。数据传输阶段,则利用遗传算法为簇首节点搜寻到基站的最佳数据传输路径。仿真结果表明,相较于LEACH、LEACH-C、K-GA等算法,BBOK-GA降低了网络能耗,提高了网络吞吐量,延长了网络生存周期。

关键词: 无线传感器网络, 生物地理学优化算法, 遗传算法, K-means算法, 分簇路由

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

中图分类号: