Next Article in Journal
The Availability of Space Service for Inter-Satellite Links in Navigation Constellations
Next Article in Special Issue
A Study of LoRa: Long Range & Low Power Networks for the Internet of Things
Previous Article in Journal
A Hybrid Vehicle Detection Method Based on Viola-Jones and HOG + SVM from UAV Images
Previous Article in Special Issue
Exploiting Outage and Error Probability of Cooperative Incremental Relaying in Underwater Wireless Sensor Networks
Article Menu

Export Article

Open AccessArticle
Sensors 2016, 16(8), 1318; doi:10.3390/s16081318

CS2-Collector: A New Approach for Data Collection in Wireless Sensor Networks Based on Two-Dimensional Compressive Sensing

1
College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China
2
School of Computer Science and Technology, Shandong University, Jinan 250100, China
3
Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK
*
Author to whom correspondence should be addressed.
Academic Editors: Dongkyun Kim and Houbing Song
Received: 28 June 2016 / Revised: 7 August 2016 / Accepted: 15 August 2016 / Published: 19 August 2016
View Full-Text   |   Download PDF [1314 KB, uploaded 19 August 2016]   |  

Abstract

In this paper, we consider the problem of reconstructing the temporal and spatial profile of some physical phenomena monitored by large-scale Wireless Sensor Networks (WSNs) in an energy efficient manner. Compressive sensing is one of the popular choices to reduce the energy consumption of the data collection in WSNs. The existing solutions only consider sparsity of sensors’ data from either temporal or spatial dimensions. In this paper, we propose a novel data collection strategy, CS2-collector, for WSNs based on the theory of Two Dimensional Compressive Sensing (2DCS). It exploits both temporal and spatial sparsity, i.e., 2D-sparsity of WSNs and achieves significant gain on the tradeoff between the compression ratio and reconstruction accuracy as the numerical simulations and evaluations on different types of sensors’ data. More intuitively, with the same given energy budget, CS2-collector provides significantly more accurate reconstruction of the profile of the physical phenomena that are temporal-spatially sparse. View Full-Text
Keywords: two-dimensional compressive sensing; Kronecker product; wireless sensor networks two-dimensional compressive sensing; Kronecker product; wireless sensor networks
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Wang, Y.; Yang, Z.; Zhang, J.; Li, F.; Wen, H.; Shen, Y. CS2-Collector: A New Approach for Data Collection in Wireless Sensor Networks Based on Two-Dimensional Compressive Sensing. Sensors 2016, 16, 1318.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Sensors EISSN 1424-8220 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top