WSN中基于压缩感知的数据收集方案  

Data Gathering Scheme Based on Compressive Sensing in Wireless Sensor Networks

作　　者：张明[1] 朱俊平[1] 蔡骋[1] 

机构地区：[1]西北农林科技大学信息工程学院计算机科学系,陕西杨陵712100

出　　处：《计算机工程》2012年第20期68-71,共4页Computer Engineering

摘　　要：提出一种基于压缩感知的数据收集方案。依据感知数据的空间相关性分析,计算出事件发生的区域范围。基于剩余能量的成簇算法对区域范围内的节点进行分簇。各个节点将感知到的原始数据,基于压缩感知理论,进行数据的稀疏表示并采用随机高斯矩阵进行观测,将其观测值发送和存储在簇头节点上,当有移动收集者进入簇头的通信范围后,进行数据收集。理论分析和仿真实验结果表明,该方案能有效延长网络生命周期。Data collection in Wireless Sensor Network（WSN） research is the basic problem.This paper presents a data collection solution based on compressive sensing technique and mobile data collector.The regional scope of the incident is calculated by the analysis of spatial correlation of data,and a clustering algorithm is proposed based on residual energy of the nodes to carve up the region events.On this basis,each node senses the original data,based on the theory of compressed sensing.The data is sparse representation and observations by adopting Gaussian Random Matrix（GRM）,and its observations are sent and stored in its cluster head,when a mobile collector enters the cluster head communication range,achieving the data collection.Theoretical analysis and simulation experimental results show that this scheme is energy efficient,and can effectively extend the network lifetime.

关 键 词：无线传感器网络 数据收集 压缩感知 空间相关性 稀疏表示 生命周期 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]