基于IFOA优化DV-distance算法的无线传感器网络定位研究

Research on IFOA-based DV-distance algorithm for WSNs localization

对无线传感器网络节点定位问题进行研究,提出一种基于IFOA优化DV-distance算法的WSNs定位方法。针对DV-distance算法定位精度低、噪声影响大,受限于网络拓扑结构等问题,将改进的果蝇优化算法(IFOA)引入到DVdistance设计中,实现了节点位置的精确定位,为进一步提高算法定位的精度,引入动态加权修正因子,并给出动态误差修正策略,最后对WSNs节点定位问题进行实验仿真,仿真结果表明,基于IFOA优化的DV-distance定位算法较DV-distance和传统定位算法在定位精度上有明显改善。

The node localization problem for wireless sensor networks（WSNs） is studied. A DV-distance algorithm based on fruit fly optimization algorithm for WANs localization is proposed. Since the DV-distance localization algorithm has the defect of low localization precision,is influenced by noise easily,and restricted to the network topology structure,an improved fruit fly optimization algorithm（IFOA）is introduced into the DV-distance algorithm to realize the accurate localization of the node position. In order to improve the algorithm localization accuracy further,the dynamic weighted correction factor is introduced into the algorithm,and the dynamic error correction strategy is given. The simulation experiment was performed for WSNs node localization. The simulation results show that the positioning accuracy of the improved DV-distance localization algorithm is significantly improved than that of the DV-distance and traditional localization algorithms.