摘要
针对无线传感网络(Wireless Sensor Networks,WSNs)监测突发事件及节点能量受限问题,提出基于压缩抽样的事件检测算法。该算法充分利用压缩感知技术在以稀疏数据重构原始数据方面上的优势。先收集活动节点数据,再对这些数据进行随机抽样。再由簇头利用压缩感知技术融合这些抽样数据,进而减少节点传输的数据量,提高网络寿命。同时,该算法引用伪概率-感测模型。通过该模型确保对事件的联合感测概率总是大于预定的阈值。仿真结果表明,提出的算法在网络寿命、能耗方面具有良好的性能。
In view of unexpected events and node energy limitation in Wireless Sensor Networks(WSNs),Compressed Sampling-based Event Detection algorithm is proposed in this paper.This algorithm makes full use of the advantages of compressed sensing technology in the reconstruction of original data with sparse data.First,the data of activity nodes are collected,and then these data are randomly sampled.Then the cluster head integrates these sampling data by using compressed sensing technology,which can reduce the amount of data transmitted by nodes and improve the network lifetime.In addition,a pseudo probabilistic model is proposed and ensuring that the joint sensing probability of the event is always more than the predefined threshold.Simulation results show that the proposed algorithm has good performance in network lifetime and energy consumption.
作者
付朝晖
谢英辉
FU Zhao-hui;XIE Ying-hui(Changsha Social Work College,Changsha 410004,China)
出处
《中国电子科学研究院学报》
北大核心
2020年第9期905-909,共5页
Journal of China Academy of Electronics and Information Technology
关键词
无线传感网络
事件检测
压缩感知
感测模型
网络寿命
wireless sensor networks
event detection
compressed sensing
sensing model
network lifetime
