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dc.contributor.authorMidoglu, Cise
dc.contributor.authorAvelino, Mariana
dc.contributor.authorGopalakrishnan, Shri Hari
dc.contributor.authorPham, Stefan
dc.contributor.authorHalvorsen, Pål
dc.date.accessioned2023-04-19T09:00:06Z
dc.date.available2023-04-19T09:00:06Z
dc.date.created2023-01-06T11:51:19Z
dc.date.issued2022
dc.identifier.isbn978-1-4503-9222-8
dc.identifier.urihttps://hdl.handle.net/11250/3063753
dc.description.abstractIn today’s complex OTT multimedia streaming ecosystem, the task of ensuring the best streaming experience to end-users requires extensive monitoring, and such monitoring information is relevant to various stakeholders including content providers, CDN providers, network operators, device vendors, developers, and researchers. Streaming analytics solutions address this need by aggregating performance information across streaming sessions, to be presented in ways that help improve the end-to-end delivery. In this paper, we provide an analysis of the state of the art in commercial streaming analytics solutions. We consider five products as representatives, and identify potential improvements with respect to terminology, QoE representation, standardization and interoperability, and collaboration with academia and the developer community.en_US
dc.language.isoengen_US
dc.publisherAssociation for Computing Machinery (ACM)en_US
dc.relation.ispartofMHV '22: Proceedings of the 1st Mile-High Video Conference
dc.relation.ispartofseriesMHV: Mile-High Video;MHV '22: Proceedings of the 1st Mile-High Video Conference
dc.rightsNavngivelse 4.0 Internasjonal*
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/deed.no*
dc.titleMultimedia streaming analytics: quo vadis?en_US
dc.typeConference objecten_US
dc.description.versionpublishedVersionen_US
cristin.ispublishedtrue
cristin.fulltextoriginal
dc.identifier.doihttps://doi.org/10.1145/3510450.3517321
dc.identifier.cristin2101959
dc.source.pagenumber62-69en_US


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