Title: A representative node selection-based data gathering method for compressive sensing in WSNs

Authors: Chengyang Xie; Jiancong Zhao; Yugang Niu

Addresses: Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology), Ministry of Education, Shanghai 200237, China ' School of Science, East China University of Science and Technology, Shanghai 200237, China ' Key Laboratory of Advanced Control and Optimization for Chemical Process (East China University of Science and Technology), Ministry of Education, Shanghai 200237, China

Abstract: 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.

Keywords: CDG; compressive data gathering; spatiotemporal correlation; RNS; representative node selection; WSNs; wireless sensor networks.

DOI: 10.1504/IJSNET.2018.094700

International Journal of Sensor Networks, 2018 Vol.28 No.1, pp.1 - 10

Received: 13 Jul 2016
Accepted: 24 Jun 2017

Published online: 08 Sep 2018 *

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