• 中国计算机学会会刊
  • 中国科技核心期刊
  • 中文核心期刊

计算机工程与科学 ›› 2021, Vol. 43 ›› Issue (07): 1210-1218.

• 计算机网络与信息安全 • 上一篇    下一篇

一种基于狼群优化的改进DV_Hop定位算法

宋玲,黄达胜   

  1. (广西大学计算机与电子信息学院,广西 南宁 530004)
  • 收稿日期:2020-09-02 修回日期:2020-11-13 接受日期:2021-07-25 出版日期:2021-07-25 发布日期:2021-08-16
  • 基金资助:
    国家自然科学基金(61762030);广西创新驱动重大专项(桂科AA17204017);广西重点研发计划(桂科AB19110050,AB16380237);广西自然科学基金(2018GXNSFAA)

An improved DV_ Hop location algorithm based on improved wolf colony algorithm

SONG Ling,HUANG Da-sheng   

  1. (School of Computer and Electronic Information,Guangxi University,Nanning 530004,China)
  • Received:2020-09-02 Revised:2020-11-13 Accepted:2021-07-25 Online:2021-07-25 Published:2021-08-16

摘要: DV_Hop算法是经典的无需测距的无线传感器网络节点定位算法之一,但由于节点分布不均匀,由平均跳距计算出的未知节点与锚节点的距离跟实际距离差距较大,导致其定位精度不高。针对这一问题,借助于狼群算法需要的计算参数较少以及具有良好的寻优精度的特点,提出一种基于优化狼群算法(IWCA)的DV_Hop算法(IWCADV_Hop)。首先将DV_Hop算法的估计距离进行优化,对于距离锚节点跳数为1的未知节点,用RSSI方法直接求出它与锚节点的距离,从而减小估计距离的误差;其次,由于狼群算法容易陷入局部最优,提出优化狼群算法(IWCA),采用模拟退火的思想在探狼k次迭代未改变位置时,允许以一定概率向效果差的方向游走,游走方式采用混沌映射的方式;最后,将IWCA算法应用到节点定位的计算阶段,从而减小DV_Hop算法计算节点位置时产生的误差。理论分析与仿真实验表明,与同类算法相比,本文提出的IWCADV_Hop算法能提高无线传感器网络节点定位的准确性。


关键词: 无线传感器网络, 节点定位, DV_Hop, 狼群算法

Abstract: DV_hop algorithm is one of the classical range-free sensor node location algorithms. However, due to the uneven distribution of nodes, the distance between the unknown nodes and the anchor nodes calculated by the average hop distance is far from the actual distance, resulting in the lack of positioning accuracy. To solve this problem, an improved DV_Hop algorithm based on improved wolf colony algorithm (IWCA) is proposed by virtue of the fact that wolf colony algorithm needs less calculation parameters and has good optimization accuracy. Firstly, the estimated distance of DV_hop algorithm is optimized. For the unknown node with 1 hop from anchor nodes, the distance between itself and anchor nodes is directly calculated by RSSI method, so as to reduce the error of estimated distance. Secondly, because the wolf colony algorithm is easy to fall into the local optimum, an improved wolf colony algorithm (IWCA) is proposed. The idea of simulated annealing is adopted. When the position of N iterations of probe wolf is not changed, it is allowed to swim in the direction of poor effect with a certain probability. The way of swimming is chaos mapping. Finally, The IWCA is applied to the calculation of node location, so as to reduce the error of DV_Hop algorithm when calculating node location. Theoretical analysis and simulation experiments show that compared with similar algorithms, IWCADV_Hop can improve the accuracy of sensor network node location.

Key words: wireless sensor network, node location, DV_Hop, wolf colony algorithm