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dc.contributor.authorMillán Marco, Pere
dc.contributor.authorAliagas Castell, Carles
dc.contributor.authorMolina Clemente, Carlos Maria
dc.contributor.authorDimogerontakis, Emmanouil
dc.contributor.authorMeseguer Pallarès, Roc
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2019-07-26T10:18:51Z
dc.date.available2019-07-26T10:18:51Z
dc.date.issued2019-05-01
dc.identifier.citationMillán, P. [et al.]. Time series analysis to predict end-to-end quality of wireless community networks. "Electronics", 1 Maig 2019, vol. 8, núm. 5, p. 1-23.
dc.identifier.issn2079-9292
dc.identifier.urihttp://hdl.handle.net/2117/166928
dc.description.abstractCommunity Networks have been around us for decades being initially deployed in the USA and Europe. They were designed by individuals to provide open and free “do it yourself” Internet access to other individuals in the same community and geographic area. In recent years, they have evolved as a viable solution to provide Internet access in developing countries and rural areas. Their social impact is measurable, as the community is provided with the right and opportunity of communication. Community networks combine wired and wireless links, and the nature of the wireless medium is unreliable. This poses several challenges to the routing protocol. For instance, Link-State routing protocols deal with End-to-End Quality tracking to select paths that maximize the delivery rate and minimize traffic congestion. In this work, we focused on End-to-End Quality prediction by means of time-series analysis to foresee which paths are more likely to change their quality. We show that it is possible to accurately predict End-to-End Quality with a small Mean Absolute Error in the routing layer of large-scale, distributed, and decentralized networks. In particular, we analyzed the path ETX behavior and properties to better identify the best prediction algorithm. We also analyzed the End-to-End Quality prediction accuracy some steps ahead in the future, as well as its dependency on the hour of the day. Besides, we quantified the computational cost of the prediction. Finally, we evaluated the impact of the usage for routing of our approach versus a simplified OLSR (ETX + Dijkstra) on an overloaded network.
dc.format.extent23 p.
dc.language.isoeng
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 Spain
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Telemàtica i xarxes d'ordinadors
dc.subject.lcshWireless LANs
dc.subject.otherCommunity networks
dc.subject.otherEnd-to-end quality prediction
dc.subject.otherTime-series analysis
dc.titleTime series analysis to predict end-to-end quality of wireless community networks
dc.typeArticle
dc.subject.lemacXarxes locals sense fil Wi-Fi
dc.contributor.groupUniversitat Politècnica de Catalunya. CNDS - Xarxes de Computadors i Sistemes Distribuïts
dc.identifier.doi10.3390/electronics8050578
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttps://www.mdpi.com/2079-9292/8/5/578
dc.rights.accessOpen Access
drac.iddocument25419441
dc.description.versionPostprint (published version)
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2016-77836-C2-2-R
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2016-77836-C2-1-R
dc.relation.projectidinfo:eu-repo/grantAgreement/MINECO/1PE/TIN2016-75344-R
upcommons.citation.authorMillán, P.; Aliagas, C.; Molina, C.; Dimogerontakis, E.; Meseguer, R.
upcommons.citation.publishedtrue
upcommons.citation.publicationNameElectronics
upcommons.citation.volume8
upcommons.citation.number5
upcommons.citation.startingPage1
upcommons.citation.endingPage23


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Except where otherwise noted, content on this work is licensed under a Creative Commons license: Attribution-NonCommercial-NoDerivs 3.0 Spain