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dc.contributor.authorRazzaque, Mohammad Abdur
dc.contributor.authorDobson, Simon Andrew
dc.identifier.citationRazzaque , M A & Dobson , S A 2014 , ' Energy-efficient sensing in wireless sensor networks using compressed sensing ' , Sensors , vol. 14 , no. 2 , pp. 2822-2859 .
dc.identifier.otherPURE: 89290452
dc.identifier.otherPURE UUID: 6e75f22c-e3e2-4b26-8882-604a741926b0
dc.identifier.otherScopus: 84893935371
dc.identifier.otherWOS: 000335887900047
dc.identifier.otherORCID: /0000-0001-9633-2103/work/70234176
dc.description.abstractSensing 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.
dc.rights(c) 2014 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (
dc.subjectSensing energyen
dc.subjectCompressed sensingen
dc.subjectAdaptive samplingen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.titleEnergy-efficient sensing in wireless sensor networks using compressed sensingen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.description.statusPeer revieweden

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