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dc.contributor.authorDehwah, Ahmad H.
dc.contributor.authorElmetennani, Shahrazed
dc.contributor.authorClaudel, Christian
dc.date.accessioned2017-04-20T08:08:16Z
dc.date.available2017-04-20T08:08:16Z
dc.date.issued2017-04-11
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.
dc.identifier.issn1084-8045
dc.identifier.doi10.1016/j.jnca.2017.04.003
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.
dc.description.sponsorshipThe research reported in this manuscript is supported by King Abdullah University of Science and Technology (KAUST).
dc.publisherElsevier BV
dc.relation.urlhttp://www.sciencedirect.com/science/article/pii/S108480451730142X
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/
dc.subjectSolar energy forecast
dc.subjectWCMA
dc.subjectSolar powered WSN
dc.titleUD-WCMA: An Energy Estimation and Forecast Scheme for Solar Powered Wireless Sensor Networks
dc.typeArticle
dc.contributor.departmentComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
dc.contributor.departmentElectrical Engineering Program
dc.contributor.departmentEntrepreneurship Center
dc.identifier.journalJournal of Network and Computer Applications
dc.eprint.versionPost-print
dc.contributor.institutionCivil Architectural and Environmental Engineering, The University of Texas at Austin, Austin, TX
kaust.personDehwah, Ahmad H.
kaust.personElmetennani, Shahrazed
refterms.dateFOA2019-04-11T00:00:00Z
dc.date.published-online2017-04-11
dc.date.published-print2017-07


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