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dc.contributor.authorLaine, Sanna
dc.contributor.authorHakala, Ismo
dc.date.accessioned2022-01-31T09:38:01Z
dc.date.available2022-01-31T09:38:01Z
dc.date.issued2022
dc.identifier.citationLaine, S., & Hakala, I. (2022). Network Capacity Estimators Predicting QoE in HTTP Adaptive Streaming. <i>IEEE Access</i>, <i>10</i>, 9817-9829. <a href="https://doi.org/10.1109/ACCESS.2022.3145185" target="_blank">https://doi.org/10.1109/ACCESS.2022.3145185</a>
dc.identifier.otherCONVID_104043379
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/79569
dc.description.abstractThe aim of adaptive HTTP streaming technology is preserving the best possible video streaming quality for viewers in heterogeneous network conditions. This can be achieved by making multiple quality versions of the video available. Switching between versions during playback should be imperceptible and fluent. The decision about quality-level switching is typically based on network capacity estimation and buffer occupancy, which predict the risk of stalling. Since quality-level switching and stalling are directly evident to the user, they are often classified as influence factors of quality of experience (QoE). In this paper, we observe different network capacity estimators and buffer behavior in limited network conditions and study how the estimators predict QoE. The challenges of variable bitrate (VBR)-encoded video are considered. We also propose two new estimators to predict QoE. One compares segment fetch time to segment playback time, while the other explores the difference of throughput and average download rate. As segment duration may influence HTTP adaptive streaming (HAS) playback in unstable conditions, the findings are tested with four segment lengths. Moreover, streaming quality is analyzed in a testbed using two popular web players to reveal possible effects of the players’ features.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)
dc.relation.ispartofseriesIEEE Access
dc.rightsCC BY 4.0
dc.subject.otherstreaming media
dc.subject.otherHTTP adaptive streaming
dc.subject.otherbit rate
dc.subject.otherquality of experience
dc.subject.otherplayer performance
dc.subject.otherquality of service
dc.subject.otherthroughput
dc.subject.otherswitches
dc.subject.otherestimation
dc.subject.otherbandwidth
dc.subject.otheradaptive algorithm
dc.subject.othernetwork capacity estimators
dc.titleNetwork Capacity Estimators Predicting QoE in HTTP Adaptive Streaming
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202201311336
dc.contributor.laitosKokkolan yliopistokeskus Chydeniusfi
dc.contributor.laitosKokkola University Consortium Chydeniusen
dc.contributor.oppiaineTekniikkafi
dc.contributor.oppiaineInformaatioteknologian yksikköfi
dc.contributor.oppiaineEngineeringen
dc.contributor.oppiaineThe Unit of Information Technologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.type.coarhttp://purl.org/coar/resource_type/c_2df8fbb1
dc.description.reviewstatuspeerReviewed
dc.format.pagerange9817-9829
dc.relation.issn2169-3536
dc.relation.volume10
dc.type.versionpublishedVersion
dc.rights.copyright© IEEE, 2022
dc.rights.accesslevelopenAccessfi
dc.subject.ysolaatu
dc.subject.ysovaihtoehdot
dc.subject.ysosuoratoisto
dc.subject.ysokäyttäjäkokemus
dc.subject.ysosuorituskyky
dc.subject.ysoalgoritmit
dc.subject.ysovideo
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p5029
jyx.subject.urihttp://www.yso.fi/onto/yso/p22310
jyx.subject.urihttp://www.yso.fi/onto/yso/p25409
jyx.subject.urihttp://www.yso.fi/onto/yso/p25337
jyx.subject.urihttp://www.yso.fi/onto/yso/p14041
jyx.subject.urihttp://www.yso.fi/onto/yso/p14524
jyx.subject.urihttp://www.yso.fi/onto/yso/p8368
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1109/ACCESS.2022.3145185
dc.type.okmA1


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Except where otherwise noted, this item's license is described as CC BY 4.0