Comparative Study of Distributed Estimation Precision by Average Consensus Weight Models

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dc.contributor.authorKenyeres, Martincs
dc.contributor.authorKenyeres, Jozefcs
dc.coverage.issue4cs
dc.coverage.volume13cs
dc.date.issued2017-12-21cs
dc.description.abstractDistributed algorithms for an aggregate function estimation are an important complement of many real-life applications based on wireless sensor networks. Achieving a high precision of an estimation in a shorter time can optimize the overall energy consumption. Therefore, the choice of a proper distributed algorithm is an important part of an application design. In this study, we focus our attention on the average consensus algorithm and evaluate six weight models appropriate for the implementation into real-life applications. Our aim is to find the most suitable model in terms of the estimation precision in various phases of the algorithm. We examine the deviation of the least precise estimate over iterations for a Gaussian, a Uniform and a Bernoulli distribution of the initial states in strongly and weakly connected networks with a randomly generated topology. We examine which model is the most and the least precise in various phases. Based on these findings, we determine the most suitable model for real-life applications.en
dc.formattextcs
dc.format.extent165-177cs
dc.format.mimetypeapplication/pdfcs
dc.identifier.citationJournal of Communications Software and Systems. 2017, vol. 13, issue 4, p. 165-177.en
dc.identifier.doi10.24138/jcomss.v13i4.405cs
dc.identifier.issn1845-6421cs
dc.identifier.other142576cs
dc.identifier.urihttp://hdl.handle.net/11012/84113
dc.language.isoencs
dc.publisherCroatian Communications and Information Societycs
dc.relation.ispartofJournal of Communications Software and Systemscs
dc.relation.urihttps://jcomss.fesb.unist.hr/index.php/jcomss/article/view/405cs
dc.rightsCreative Commons Attribution-NonCommercial 4.0 Internationalcs
dc.rights.accessopenAccesscs
dc.rights.sherpahttp://www.sherpa.ac.uk/romeo/issn/1845-6421/cs
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/cs
dc.subjectDistributed computingen
dc.subjectwireless sensor networksen
dc.subjectaverage consensus algorithmen
dc.subjectestimation precisionen
dc.titleComparative Study of Distributed Estimation Precision by Average Consensus Weight Modelsen
dc.type.driverarticleen
dc.type.statusPeer-revieweden
dc.type.versionpublishedVersionen
sync.item.dbidVAV-142576en
sync.item.dbtypeVAVen
sync.item.insts2025.02.03 15:39:22en
sync.item.modts2025.01.17 15:30:19en
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. Ústav telekomunikacícs
thesis.grantorVysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií. oddělení-TKO-SIXcs
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