UD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks

Handle URI:
http://hdl.handle.net/10754/623267
Title:
UD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks
Authors:
Dehwah, Ahmad H.; Elmetennani, Shahrazed ( 0000-0001-7608-8713 ) ; Claudel, Christian
Abstract:
Energy estimation and forecast represents an important role for energy management in solar-powered wireless sensor networks (WSNs). In general, the energy in such networks is managed over a finite time horizon in the future based on input solar power forecasts to enable continuous operation of the WSNs and achieve the sensing objectives while ensuring that no node runs out of energy. In this article, we propose a dynamic version of the weather conditioned moving average technique (UD-WCMA) to estimate and predict the variations of the solar power in a wireless sensor network. The presented approach combines the information from the real-time measurement data and a set of stored profiles representing the energy patterns in the WSNs location to update the prediction model. The UD-WCMA scheme is based on adaptive weighting parameters depending on the weather changes which makes it flexible compared to the existing estimation schemes without any precalibration. A performance analysis has been performed considering real irradiance profiles to assess the UD-WCMA prediction accuracy. Comparative numerical tests to standard forecasting schemes (EWMA, WCMA, and Pro-Energy) shows the outperformance of the new algorithm. The experimental validation has proven the interesting features of the UD-WCMA in real time low power sensor nodes.
KAUST Department:
Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Citation:
Dehwah AH, Elmetennani S, Claudel C (2017) UD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks. Journal of Network and Computer Applications. Available: http://dx.doi.org/10.1016/j.jnca.2017.04.003.
Publisher:
Elsevier BV
Journal:
Journal of Network and Computer Applications
Issue Date:
11-Apr-2017
DOI:
10.1016/j.jnca.2017.04.003
Type:
Article
ISSN:
1084-8045
Sponsors:
The research reported in this manuscript is supported by King Abdullah University of Science and Technology (KAUST).
Additional Links:
http://www.sciencedirect.com/science/article/pii/S108480451730142X
Appears in Collections:
Articles; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division

Full metadata record

DC FieldValue Language
dc.contributor.authorDehwah, Ahmad H.en
dc.contributor.authorElmetennani, Shahrazeden
dc.contributor.authorClaudel, Christianen
dc.date.accessioned2017-04-20T08:08:16Z-
dc.date.available2017-04-20T08:08:16Z-
dc.date.issued2017-04-11en
dc.identifier.citationDehwah AH, Elmetennani S, Claudel C (2017) UD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks. Journal of Network and Computer Applications. Available: http://dx.doi.org/10.1016/j.jnca.2017.04.003.en
dc.identifier.issn1084-8045en
dc.identifier.doi10.1016/j.jnca.2017.04.003en
dc.identifier.urihttp://hdl.handle.net/10754/623267-
dc.description.abstractEnergy estimation and forecast represents an important role for energy management in solar-powered wireless sensor networks (WSNs). In general, the energy in such networks is managed over a finite time horizon in the future based on input solar power forecasts to enable continuous operation of the WSNs and achieve the sensing objectives while ensuring that no node runs out of energy. In this article, we propose a dynamic version of the weather conditioned moving average technique (UD-WCMA) to estimate and predict the variations of the solar power in a wireless sensor network. The presented approach combines the information from the real-time measurement data and a set of stored profiles representing the energy patterns in the WSNs location to update the prediction model. The UD-WCMA scheme is based on adaptive weighting parameters depending on the weather changes which makes it flexible compared to the existing estimation schemes without any precalibration. A performance analysis has been performed considering real irradiance profiles to assess the UD-WCMA prediction accuracy. Comparative numerical tests to standard forecasting schemes (EWMA, WCMA, and Pro-Energy) shows the outperformance of the new algorithm. The experimental validation has proven the interesting features of the UD-WCMA in real time low power sensor nodes.en
dc.description.sponsorshipThe research reported in this manuscript is supported by King Abdullah University of Science and Technology (KAUST).en
dc.publisherElsevier BVen
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S108480451730142Xen
dc.rightsNOTICE: this is the author’s version of a work that was accepted for publication in Journal of Network and Computer Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Network and Computer Applications, [, , (2017-04-11)] DOI: 10.1016/j.jnca.2017.04.003 . © 2017. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/en
dc.subjectSolar energy forecasten
dc.subjectWCMAen
dc.subjectSolar powered WSNen
dc.titleUD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networksen
dc.typeArticleen
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Divisionen
dc.identifier.journalJournal of Network and Computer Applicationsen
dc.eprint.versionPost-printen
dc.contributor.institutionCivil Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TXen
kaust.authorDehwah, Ahmad H.en
kaust.authorElmetennani, Shahrazeden
All Items in KAUST are protected by copyright, with all rights reserved, unless otherwise indicated.