基于罚函数与水波优化的WSN定位算法

doi:10.13190/j.jbupt.2019-193

北京邮电大学学报 ›› 2020, Vol. 43 ›› Issue (4): 106-112.doi: 10.13190/j.jbupt.2019-193

基于罚函数与水波优化的WSN定位算法

余修武^1,2,3, 张可¹, 刘永^1,2,3

1. 南华大学资源环境与安全工程学院, 衡阳 421001;
2. 湖南省铀尾矿库退役治理技术工程技术研究中心, 衡阳 421001;
3. 铀矿冶放射性控制技术湖南省工程研究中心, 衡阳 421001

收稿日期:2019-09-12 发布日期:2020-08-15
通讯作者: 张可(1997-),男,硕士生,E-mail:zhangkeblue@163.com. E-mail:zhangkeblue@163.com
作者简介:余修武(1976-),男,教授,硕士生导师.
基金资助:
国家自然科学基金项目（11875164）；国家应急管理部安全生产重特大事故防治关键技术科技项目（hunan-0001-2018AQ）；湖南省重点研发计划项目（2018SK2055）；铀矿冶放射性控制技术湖南省工程研究中心、湖南省铀尾矿库退役治理技术工程技术研究中心联合开放课题重点项目（2018YKZX1009）

Localization Algorithm Based on Penalty Function and Water Wave Optimization for WSN

YU Xiu-wu^1,2,3, ZHANG Ke¹, LIU Yong^1,2,3

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 Technology, Hengyang 421001, China;
3. Hunan Province Engineering Research Center of Radioactive Control Technology in Uranium Mining and Metallurgy, Hengyang 421001, China

Received:2019-09-12 Published:2020-08-15

摘要/Abstract

摘要： 为了提高启发式定位算法的搜索效率和定位精度，提出了基于罚函数和水波优化的无线传感器网络（WSN）定位算法.首先利用bounding-box方法构造罚函数，提高算法搜索的效率和定位精度；然后利用动态学习策略对传统水波优化算法的传播阶段进行改进，促使个体对周围优秀个体的学习，并通过动态波高提高个体在后期局部搜索的概率，进一步提高搜索效率和求解精度.仿真结果表明，罚函数策略与改进水波优化算法能提高搜索效率和定位精度，所提出的算法在WSN节点定位上有较好的可行性和有效性.

关键词: 无线传感器网络, 水波优化, 罚函数, 节点定位

Abstract: In order to improve the search efficiency and localization accuracy of the heuristic localization algorithm, a localization algorithm base on penalty function and water wave optimization for wireless sensor network (WSN) is proposed. Firstly, the proposed algorithm uses the bounding-box method to construct the penalty function, which improves the water wave optimization algorithm's searching efficiency. Then the dynamic learning strategy is used to improve the propagation stage of the traditional water wave optimization algorithm, which encourages the individual to learn from the surrounding excellent individuals. And the dynamic wave height is introduced to enhance the individual's local search probability in late stage. Simulations show that the penalty function strategy and the improved water wave optimization algorithm can improve the search efficiency and positioning accuracy. The proposed algorithm has good feasibility and effectiveness in WSN node location.

Key words: wireless sensor network, water wave optimization, penalty function, node localization

中图分类号:

TN929.5

余修武, 张可, 刘永. 基于罚函数与水波优化的WSN定位算法[J]. 北京邮电大学学报, 2020, 43(4): 106-112.

YU Xiu-wu, ZHANG Ke, LIU Yong. Localization Algorithm Based on Penalty Function and Water Wave Optimization for WSN[J]. Journal of Beijing University of Posts and Telecommunications, 2020, 43(4): 106-112.

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基于罚函数与水波优化的WSN定位算法

Localization Algorithm Based on Penalty Function and Water Wave Optimization for WSN

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