基于差分进化和人工蜂群混合策略的DV-Hop改进算法  

DV-Hop improved algorithm based on fusion of differential evolution algorithm and artificial bee colony algorithm

作　　者：赵宏才[1] 赵晓杰[1,2] 王茂励[2] 孟庆龙[2] 

机构地区：[1]青岛理工大学自动化学院,山东青岛266033 [2]山东省计算中心(国家超级计算济南中心)山东省计算机网络重点实验室,山东济南250014

出　　处：《现代电子技术》2017年第15期129-132,共4页Modern Electronics Technique

基　　金：国家自然科学基金(51475251);山东省自然科学基金(ZR2014EEM024);山东省科技重大专项(2015ZDZX10002)

摘　　要：为了解决无线传感器网络依靠DV-Hop算法定位过程中存在误差偏高的问题,将人工蜂群算法和差分进化算法融合,引入传统DV-Hop算法中,提出一种HDV-Hop算法。该算法在继承经典DV-Hop算法的前提下,获取锚节点的信息及平均跳距距离,在未知节点定位阶段引入混合策略的目标函数,优化搜索算法,提高定位精度,完成对未知节点的定位。仿真分析表明,该算法相比于DV-Hop算法和基于人工蜂群的定位算法能有效降低定位误差,提高稳定性。In order to solve the big error of the wireless sensor network （WSN） relying on DV-Hop algorithm in position process, the artificial bee colony algorithm and differential evolution algorithm are fused, and introduced into the traditional DV- Hop algorithm to propose a HDV-Hop algorithm. Under the premise of inheriting the classic DV-Hop algorithm, the objective function of the mixed strategy is introduced into the positioning stage of unknown node after getting the anchor node information and average hop distance, the search algorithm is optimized, and the positioning accuracy is improved to locate the unknown nodes. The simulation analysis results show that, in comparison with the DV-Hop algorithm and positioning algorithm based on artificial bee colony, the proposed algorithm can reduce the positioning error effectively, and improve the stability.

关 键 词：DV-HOP算法 人工蜂群 差分进化 定位 

分 类 号：TN911-34[电子电信—通信与信息系统] TP393[电子电信—信息与通信工程]