WSN中改进的基于压缩感知的分簇数据采集算法  

Improved Clustering Algorithm for Data Acquisition Based on Compressed Sensing in WSN

作　　者：谢昕[1] 汪加楠 姜楠[1] 黄晓生[2] 葛松林 Xie Xin;Wang Jianan;Jiang Nan;Huang Xiaosheng;Ge Songlin(East China Jiaotong University 1. School of Information Engineering;School of Software Engineering, Nanchang 330013, China)

机构地区：[1]华东交通大学信息工程学院,江西南昌330013 [2]华东交通大学软件工程学院,江西南昌330013

出　　处：《华东交通大学学报》2018年第2期113-119,共7页Journal of East China Jiaotong University

基　　金：国家自然科学基金项目(61762037;61763011;41402290;61462028);江西省科技厅重点研发计划(20151BBE50055);江西省教育厅科技项目(GJJ150541);南昌市科技局知识创新团队项目(2016T75)

摘　　要：WSNs中节点的能量受限,为节约网络节点的功耗,提出了一种将LEACH模型和CS理论相结合的基于节点时空相关性的压缩感知算法。LEACH算法对网络节点进行分簇并选择簇首,然后,采用CS理论对簇首节点进行采样,将采样后的数据通过多跳路由的方法传至远端的汇聚节点,最后,汇聚节点对来自簇首的少量数据采用重构算法以对原始信号进行精确恢复。仿真结果表明,该方法有效减小了数据传输量,降低了网络节点的功耗,延缓了网络寿命。The energy of the sensor network nodes is limited, and in order to save the energy consumption of the sensor nodes, an improved compressed sensing algorithm combining the LEACH model with the CS theory based on the spatial-temporal correlation of nodes was proposed. The LEACH algorithm was used to cluster the network nodes and select the cluster head. Then, the cluster head node was sampled by the compressed sensing theory. The sampled data was passed to the remote sink node through multi-hop routing. Finally, a small amount of data from the cluster head used a reconstruction algorithm to accurately recover the original signal. The simulation results show that this method can effectively reduce the amount of data transmission, save the energy consumption of nodes and prolong the lifetime of the wireless sensor network.

关 键 词：无线传感器网络 压缩感知 LEACH协议 时空相关性 

分 类 号：TP393.4[自动化与计算机技术—计算机应用技术]