遗传算法的DV-Hop算法改进  

An improved DV-Hop algorithm based on genetic algorithm

作　　者：张万礼[1] 宋启祥[1] 

机构地区：[1]宿州学院智能信息处理实验室,安徽宿州234000

出　　处：《重庆大学学报（自然科学版）》2015年第3期159-166,共8页Journal of Chongqing University

基　　金：国家科技支撑计划项目(2012BAD35B02);安徽省青年人才基金重点项目(2013SQRL083ZD);宿州学院科研平台开放课题(2012YKE38);安徽高校省级自然科学研究重点项目(KJ2014A247)~~

摘　　要：DV-Hop算法中,平均每跳距离是影响定位精度的因素之一。针对平均每跳距离带来的定位误差,对锚节点和未知节点的平均每跳距离进行了改进和优化。首先引入遗传算法计算锚节点的平均每跳距离;然后利用跳数小于等于3的锚节点的平均每跳距离加权处理未知节点的平均每跳距离,减少平均每跳距离带来的误差。仿真结果表明,在不增加硬件开销的基础上,改进算法能够有效提高算法的定位精度,并且具有较好的稳定性。The average per-hop distance is one of the factors which affect the positioning accuracy in DVHop algorithm.Aiming at positioning errors caused by the average distance per hop,the average distance per hop of anchor nodes and unknown nodes have been improved and optimized in this paper.First,the average per hop distance of anchor nodes is computed by introducing genetic algorithm;Then the average distance per hop of the unknown node is weighted by using the average distance per hop of anchor nodes which hop count is less than or equal to 3to reduce errors caused average distance per hop.Ultimately the accuracy of positioning is improved.Simulation results show that without additional hardware cost,the improved algorithm can effectively improve the positioning accuracy of the algorithm and has good stability.

关 键 词：无线传感器网络 DV-HOP算法 节点定位 遗传算法 平均每跳距离 定位误差 

分 类 号：TD421[矿业工程—矿山机电]