基于人工蜂群算法的DV-Hop定位改进

针对无线传感器网络无需测距依赖的DV-Hop定位算法节点定位精度不高的问题,将鲁棒性强、收敛速度快且全局寻优性能优异的人工蜂群算法引入到DV-Hop算法的设计中,提出了一种ABDV-Hop(Artificial Bee ColonyDV-Hop)算法。该算法在传统DV-Hop算法的基础上,利用节点间的距离和锚节点的位置信息,在DV-Hop算法的最后阶段,通过建立目标优化函数,实现对未知节点坐标的估计。仿真结果表明,与传统DV-Hop算法相比,在不增加传感器节点的硬件开销的基础上,改进算法能有效降低定位误差。

Improvement of DV-Hop Localization Based on Artificial Bee Colony Algorithm

With regard to the problem that the typical rangcfrec localization algorithm of DV-Hop for wireless sensor networks has low localization accuracy, the artificial bee colony algorithm with good robust, high convergence speed and outstanding performance on solving global optimization problems was applied to the design of DV-Hop algorithm and an improved algorithm named as ABDV-Hop(Artificial Bee Colony DV-Hop) was proposed. Based on the original DV-Hop algorithm, the improved algorithm uses the information of distance between the nodes as well as the location of beacon nodes.Through establishing the optimization function, the location of unknown nodes is estimated at the final stage of the algorithm. The results show that the proposed method can significantly reduce positioning error compared with the original DV-Hop algorithm without increasing the hardware overhead of sensor nodes.