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Sensors 2014, 14(2), 2822-2859; doi:10.3390/s140202822

Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing

1
Faculty of Computing, Universiti Teknologi Malaysia, Skudai, JB 81310, Malaysia
2
School of Computer Science, University of St Andrews, KY16 9SX, Scotland, UK
*
Author to whom correspondence should be addressed.
Received: 20 December 2013 / Revised: 25 January 2014 / Accepted: 1 February 2014 / Published: 12 February 2014
(This article belongs to the Section Sensor Networks)

Abstract

Sensing of the application environment is the main purpose of a wireless sensor network. Most existing energy management strategies and compression techniques assume that the sensing operation consumes significantly less energy than radio transmission and reception. This assumption does not hold in a number of practical applications. Sensing energy consumption in these applications may be comparable to, or even greater than, that of the radio. In this work, we support this claim by a quantitative analysis of the main operational energy costs of popular sensors, radios and sensor motes. In light of the importance of sensing level energy costs, especially for power hungry sensors, we consider compressed sensing and distributed compressed sensing as potential approaches to provide energy efficient sensing in wireless sensor networks. Numerical experiments investigating the effectiveness of compressed sensing and distributed compressed sensing using real datasets show their potential for efficient utilization of sensing and overall energy costs in wireless sensor networks. It is shown that, for some applications, compressed sensing and distributed compressed sensing can provide greater energy efficiency than transform coding and model-based adaptive sensing in wireless sensor networks.
Keywords: sensing energy; compressed sensing; adaptive sampling sensing energy; compressed sensing; adaptive sampling
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

Razzaque, M.A.; Dobson, S. Energy-Efficient Sensing in Wireless Sensor Networks Using Compressed Sensing. Sensors 2014, 14, 2822-2859.

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