WSN中事件驱动与信任分配加权的层次数据融合

Hierarchical Data Fusion Using Event-Driven and Belief Assignment in WSN

针对WSN监测突发事件及节点能量受限问题,提出了一种基于事件驱动与信任度分配加权的层次数据融合算法(EDBA)。通过设置监测阈值,仅在事件发生时,相关部分节点才进入高频次数据采集和传输的兴奋状态,其他情况节点处于低频次采集(或传输)的抑制(或活动)状态,采用证据理论及信任分配函数对网络监测数据进行多层次融合,以减少监测数据传输量。仿真表明,在通常情况下,EDBA算法能耗分别是EBPDF、LEACH的50%和21%,有效地降低了网络能耗。

In view of unexpected events and node energy limitation in WSN,a data fusion algorithm using eventdriven and belief assignment（ EDBA） is proposed.By setting monitoring threshold,only when the unexpected events occurs,the relevant nodes switching to excited state which can collect and transfer data in high frequency,in other cases,nodes keeping suppressed or active state to collect and transfer data.Monitoring data is fused through evidence theory and belief assignment function to reduce the amount of transmitted data.Simulation and analysis show that under normal circumstances,energy consumption of EDBA algorithm are respectively 50% of EBPDF and 21% of LEACH.EDBA can effectively save network energy.