文献类型：期刊文献

英文题名：A representative node selection-based data gathering method for compressive sensing in WSNs

作者：Xie, Chengyang[1];Zhao, Jiancong[2];Niu, Yugang[1]

机构：[1]East China Univ Sci & Technol, Minist Educ, Key Lab Adv Control & Optimizat Chem Proc, Shanghai 200237, Peoples R China;[2]East China Univ Sci & Technol, Sch Sci, Shanghai 200237, Peoples R China

年份：2018

卷号：28

期号：1

起止页码：1

外文期刊名：INTERNATIONAL JOURNAL OF SENSOR NETWORKS

收录：;EI(收录号：20215011304557);WOS:【SCI-EXPANDED(收录号:WOS:000444457000001)】；

基金：This work was supported in part by the National Natural Science Foundation of China (61673174) and the Program of Shanghai Academic/Technology Research Leader (16XD1421300).

语种：英文

外文关键词：CDG; compressive data gathering; spatiotemporal correlation; RNS; representative node selection; WSNs; wireless sensor networks

摘要：In traditional compressive data gathering (CDG), many rounds of data gathering are required to make sure the accuracy of reconstruction signal such that most of nodes are required to participate in data gathering. By using the spatial and temporal correlation character of sensor readings, we propose a CDG method based on representative node selection (RNS-CDG) to collect measurement vector via just one routeing tree. By means of principal component analysis (PCA) and frame potential (FP), the proposed method can select fewer representative nodes from all nodes, by which a data gathering tree will be constructed. And then, via this routeing tree, a measurement vector composed of M projections will be received by Sink for recovering signal. It is shown via simulation results that the proposed method can ensure the accuracy of data reconstruction and reduce the transmissions of network.