无线传感器网络中故障容忍的事件定位算法

Fault Tolerant Event Localization in Wireless Sensor Networks

研究无线传感器网络的事件定位问题,对SNAP(Subtract on Negative Add on Positive)[1]定位算法进行改进,提出一种定位精度更高,容错性更好的定位算法MSNAP(Modified Subtract on Negative Add on Positive)。首先,每个传感器节点监测事件信号,并将观测值与设定的阈值进行比较,如果大于阈值,节点将观测值发送给Sink节点;否则,节点保持沉默状态;基于各节点汇报的观测值,Sink节点通过对报警节点的区域的+1,不报警节点的区域-1构造似然矩阵,似然矩阵中的最大值对应的位置就是事件发生的位置。与SNAP算法相比,构造似然矩阵时,根据每个节点汇报的观测值的大小,动态地调整它们估计的事件所在区域的大小,提高事件定位精度。实验结果表明:与SNAP比较,算法有效地提高了事件定位的精度和容错性。

This paper investigates event localization in wireless sensor networks.We improve the SNAP（Subtract on Negative Add on Positive）[1] localization algorithm and propose the MSNAP（Modified Subtract on Negative Add on Positive）localization algorithm with higher localization accuracy and better performance of fault tolerance.First,every sensor node obverses the event signal and compares its observed reading with a threshold.If the reading is above the threshold,the node will send it to the sink station.Otherwise,it remains silent.Based on the observed readings which the nodes report,the sink station constructs the likelihood matrix by simply adding ±1 contributions in the area around the nodes,whose maximum value points to the event location.Compared with the SNAP algorithm,when constructing the likelihood matrix,MSNAP dynamically adjusts the size of estimated region depending on the observed readings the nodes reported.Experimental results show that the algorithm effectively improves the localization accuracy and fault tolerance.