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Sensors 2014, 14(9), 16766-16784; doi:10.3390/s140916766

WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing

1,2,3,* , 1,†
,
1,†
,
1
and
1,2,3
1
Nanjing University of Posts and Telecommunications, Nanjing 210003, China
2
Jiangsu High Technology Research Key Laboratory for Wireless Sensor Networks, Nanjing 210003, China
3
Department of Geography, University of Wisconsin-Madison, Madison, WI 53706, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 8 June 2014 / Revised: 22 August 2014 / Accepted: 26 August 2014 / Published: 9 September 2014
(This article belongs to the Special Issue Wireless Sensor Networks and the Internet of Things)
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Abstract

We address the problem of data acquisition in large distributed wireless sensor networks (WSNs). We propose a method for data acquisition using the hierarchical routing method and compressive sensing for WSNs. Only a few samples are needed to recover the original signal with high probability since sparse representation technology is exploited to capture the similarities and differences of the original signal. To collect samples effectively in WSNs, a framework for the use of the hierarchical routing method and compressive sensing is proposed, using a randomized rotation of cluster-heads to evenly distribute the energy load among the sensors in the network. Furthermore, L1-minimization and Bayesian compressed sensing are used to approximate the recovery of the original signal from the smaller number of samples with a lower signal reconstruction error. We also give an extensive validation regarding coherence, compression rate, and lifetime, based on an analysis of the theory and experiments in the environment with real world signals. The results show that our solution is effective in a large distributed network, especially for energy constrained WSNs. View Full-Text
Keywords: compressive sensing; wireless sensor networks; sparse representation; hierarchical routing method; energy efficiency compressive sensing; wireless sensor networks; sparse representation; hierarchical routing method; energy efficiency
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Zou, Z.; Hu, C.; Zhang, F.; Zhao, H.; Shen, S. WSNs Data Acquisition by Combining Hierarchical Routing Method and Compressive Sensing. Sensors 2014, 14, 16766-16784.

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