移动物联网环境下无线传感网络异常节点快速定位算法

A Fast Localization Algorithm for Abnormal Nodes in Wireless Sensor Networks in the Mobile Internet of Things Environment

为了提升无线传感网络异常节点定位精度,提出一种移动物联网环境下无线传感网络异常节点快速定位算法。通过高通图滤波器对网络信号展开处理后获取高频分量,利用高频分量划分异构哈希网络,确定子图对应输出信号的特征频率分量。通过对比疑似异常节点集合和子图节点集合进行异常节点检测。利用锚节点和未知节点之间的跳数展开区域划分,并选择对应跳距的锚节点估算展开距离。通过筛选方式排除异常因子并优化全局最优解,完成异常节点定位。实验结果表明,所提方法能够实现异常节点精准检测,检测概率高达99%以上,虚警概率最高仅为0.02%,针对不同数量的锚节点数、通信半径与未知节点数,其平均定位误差均处于5%以下,提升了系统的实用性。

To improve the accuracy of abnormal node localization in wireless sensor networks,a fast localization algorithm for abnormal nodes in wireless sensor networks in mobile IoT environments is proposed.After processing the network signal through a high pass graph filter,the high-frequency components are obtained,and the heterogeneous hash network is divided by using the high-frequency components to determine the characteristic frequency components of the output signal corresponding to the subgraph.Abnormal nodes are detected by comparing the set of suspected abnormal nodes with the set of subgraph nodes.The number of hops between anchor nodes and unknown nodes is used to expand the area division,and the corresponding anchor node with the corresponding hop distance is selected to estimate the expansion distance.Abnormal factors are excluded through filtering and the global optimal solution is optimized to complete the locali-zation of abnormal nodes.The experimental results show that the proposed method can achieve accurate detection of abnormal nodes with a detection probability of over 99%,and the highest false alarm probability is only 0.02%.For different numbers of anchor nodes,communi-cation radius,and unknown nodes,the average positioning error is below 5%,which improves the practicality of the system.