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dc.contributor.authorDimopoulos, Georgios
dc.contributor.authorLeontiadis, Ilias
dc.contributor.authorBarlet Ros, Pere
dc.contributor.authorPapagiannaki, Konstantina
dc.contributor.authorSteenkiste, Peter
dc.contributor.otherUniversitat Politècnica de Catalunya. Departament d'Arquitectura de Computadors
dc.date.accessioned2016-03-08T14:17:20Z
dc.date.issued2015
dc.identifier.citationDimopoulos, G., Leontiadis, I., Barlet, P., Papagiannaki, K., Steenkiste, P. Identifying the root cause of video streaming issues in mobile devices. A: International Conference on Emerging Networking Experiments and Technologies. "Proceedings of the 2015 ACM International Conference on Emerging Networking Experiments and Technologies: 1-4 December, 2015: Heidelberg, Germany". Heidelberg: Association for Computing Machinery (ACM), 2015.
dc.identifier.isbn978-1-4503-3412-9
dc.identifier.urihttp://hdl.handle.net/2117/83982
dc.description.abstractVideo streaming on mobile devices is prone to a multi-tude of faults and although well established video Qual-ity of Experience (QoE) metrics such as stall frequencyare a good indicator of the problems perceived by theuser, they do not provide any insights about the natureof the problem nor where it has occurred. Quantifyingthe correlation between the aforementioned faults andthe users' experience is a challenging task due the largenumber of variables and the numerous points-of-failure.To address this problem, we developed a frameworkfor diagnosing the root cause of mobile video QoE is-sues with the aid of machine learning. Our solutioncan take advantage of information collected at multiplevantage points between the video server and the mobiledevice to pinpoint the source of the problem. More-over, our design works for different video types (e.g.,bitrate, duration, ..) and contexts (e.g., wireless tech-nology, encryption, ..) After training the system witha series of simulated faults in the lab, we analyzed theperformance of each vantage point separately and whencombined, in controlled and real world deployments. Inboth cases we find that the involved entities can inde-pendently detect QoE issues and that only a few vantagepoints are required to identify a problem's location andnature
dc.language.isoeng
dc.publisherAssociation for Computing Machinery (ACM)
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/es/
dc.subjectÀrees temàtiques de la UPC::So, imatge i multimèdia::Creació multimèdia::Vídeo digital
dc.subjectÀrees temàtiques de la UPC::Enginyeria de la telecomunicació::Processament del senyal::Processament de la imatge i del senyal vídeo
dc.subject.lcshImage processing
dc.subject.lcshMobile communication systems
dc.subject.otherNetworks
dc.subject.otherNetwork performance analysis
dc.subject.otherNetwork measurement
dc.titleIdentifying the root cause of video streaming issues in mobile devices
dc.typeConference report
dc.subject.lemacImatges -- Processament
dc.subject.lemacComunicacions mòbils, Sistemes de
dc.contributor.groupUniversitat Politècnica de Catalunya. CBA - Sistemes de Comunicacions i Arquitectures de Banda Ampla
dc.identifier.doi10.1145/2716281.2836109
dc.description.peerreviewedPeer Reviewed
dc.relation.publisherversionhttp://www.tid.es/sites/526e527928a32d6a7400007f/content_entry5321ef0928a32d08900000ac/5642f1341146dda9ff001549/files/mobileVideoRCA.pdf
dc.rights.accessRestricted access - publisher's policy
drac.iddocument17530749
dc.description.versionPostprint (published version)
dc.date.lift10000-01-01
upcommons.citation.authorDimopoulos, G.; Leontiadis, I.; Barlet, P.; Papagiannaki, K.; Steenkiste, P.
upcommons.citation.contributorInternational Conference on Emerging Networking Experiments and Technologies
upcommons.citation.pubplaceHeidelberg
upcommons.citation.publishedtrue
upcommons.citation.publicationNameProceedings of the 2015 ACM International Conference on Emerging Networking Experiments and Technologies: 1-4 December, 2015: Heidelberg, Germany


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