北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2021, Vol. 44 ›› Issue (4): 75-81.doi: 10.13190/j.jbupt.2020-217

• 论文 • 上一篇    下一篇

遗传-禁忌搜索优化的三维DV-Hop定位算法

余修武1,2,3, 黄露平1, 刘永1,2,3, 余昊1, 李佩1   

  1. 1. 南华大学 资源环境与安全工程学院, 衡阳 421001;
    2. 铀矿冶放射性控制技术湖南省工程研究中心, 衡阳 421001;
    3. 湖南省铀尾矿库退役治理工程技术研究中心, 衡阳 421001
  • 收稿日期:2020-10-20 发布日期:2021-10-13
  • 通讯作者: 黄露平(1997-),女,硕士生,E-mail:853561165@qq.com. E-mail:853561165@qq.com
  • 作者简介:余修武(1976-),男,教授,硕士生导师.
  • 基金资助:
    湖南省重点研发计划项目(2018SK2055);国家自然科学基金项目(11875164)

Three-Dimensional DV-Hop Location Algorithm Based on Genetic-Tabu Search Optimization in WSN

YU Xiu-wu1,2,3, HUANG Lu-ping1, LIU Yong1,2,3, YU Hao1, LI Pei1   

  1. 1. School of Resource & Environment and Safety Engineering, University of South China, Hengyang 421001, China;
    2. Hunan Province Engineering Technology Research Center of Uranium Tailings Treatment, Hengyang 421001, China;
    3. Hunan Province Engineering Research Center of Radioactive Control Technology in Uranium Mining and Metallurgy, Hengyang 421001, China
  • Received:2020-10-20 Published:2021-10-13

摘要: 为进一步提升无线传感器网络的定位精度和稳定性,提出了一种利用遗传-禁忌搜索法改进的三维distance vector-hop (DV-Hop)定位优化算法(TDGT).首先利用最优跳数、跳数调整因子以及锚节点距离误差加权值对DV-Hop中的节点间跳数和平均跳数进行改进和修正,降低了算法的定位误差;其次将具有快速搜索能力的禁忌搜索引入遗传算法中进行寻优,提升了算法的搜索效率和定位准确性.仿真结果表明,TDGT与现有的无线传感器网络定位算法相比,具有更佳的寻优搜索能力、定位精度和稳定性.

关键词: 无线传感器网络, 节点定位, 遗传算法, 禁忌搜索, DV-Hop

Abstract: To enhance the positioning accuracy and stability of wireless sensor network (WSN), a three-dimensional dv-hop positioning optimization algorithm is proposed based on an improved genetic-tabu search method (TDGT). First, the optimal hop number, hop adjustment factor, and anchor node distance error weighted value are used to improve and modify the hop number and average hop number in dv-hop to reduce the positioning error. Then, a fast tabu search is introduced into genetic algorithm to further improve the search efficiency and positioning accuracy. The simulation results show that the TDGT algorithm has better search ability, location accuracy and stability than the existing wireless sensor network localization algorithm.

Key words: wireless sensor network, nodes positioning, genetic algorithm, tabu search, DV-Hop

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