基于灰色预测的分布式传感器网络故障检测方法

A Gray-Forecast Algorithm of Fault Detection for Wireless Sensor Networks

针对无线传感器网络节点故障原因复杂,基于灰色预测理论,提出一种故障检测方法。算法通过分析在某一采样间隔内,观测节点数据变化趋势是否与邻居节点变化趋势一致,从而确定节点是否异常。仿真实验表明,算法故障检测能力较强,且避免了节点瞬间失效情况的出现。同时该算法设计简单,易于硬件实现。

Wireless Sensor Networks （WSNs） are widely used in environmental monitoring,health care,smart home, military fields,and so on,because of its small,flexibility,low cost and unattended. And faults are common due to the bad environment and unattended. In order to ensure WSNs’service is normal,it is necessary to detect the faults. According to the complex reasons of wireless sensor network nodes failure,this paper presents a new fault detection algorithm based on based on gray prediction theory. The algorithm is that within a sample interval,it is analyzed that the observed node’s data trend is consistent with the trend of changed in the neighbour nodes to determine whether the node is abnormal. The experiment shows fault detection precision is very high,and the algorithm avoid the node instant failure. Meanwhile,the algorithm is simple,easily implemented in hardware.