Datasets for AVC (H.264) and HEVC (H.265) evaluation of dynamic adaptive streaming over HTTP (DASH)

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dc.contributor.author Quinlan, Jason J.
dc.contributor.author Zahran, Ahmed H.
dc.contributor.author Sreenan, Cormac J.
dc.date.accessioned 2017-09-21T09:27:35Z
dc.date.available 2017-09-21T09:27:35Z
dc.date.issued 2016-05-10
dc.identifier.citation Quinlan, J. J., Zahran, A. H. and Sreenan, C. J. 'Datasets for AVC (H.264) and HEVC (H.265) evaluation of dynamic adaptive streaming over HTTP (DASH)', Proceedings of the 7th International Conference on Multimedia Systems, Klagenfurt, Austria. 2910625: ACM, 1-6. doi:10.1145/2910017.2910625 en
dc.identifier.startpage 1 en
dc.identifier.endpage 6 en
dc.identifier.isbn 978-1-4503-4297-1/16/05
dc.identifier.uri http://hdl.handle.net/10468/4755
dc.identifier.doi 10.1145/2910017.2910625
dc.description.abstract In this paper we present datasets for both trace-based simulation and real-time testbed evaluation of Dynamic Adaptive Streaming over HTTP (DASH). Our trace-based simulation dataset provides a means of evaluation in frameworks such as NS-2 and NS-3, while our testbed evaluation dataset offers a means of analysing the delivery of content over a physical network and associated adaptation mechanisms at the client. Our datasets are available in both H.264 and H.265 with encoding rates comparative to the representations and resolutions of content distribution providers such as Netflix, Hulu and YouTube. The goal of our dataset is to provide researchers with a sufficiently large dataset, in both number, and duration, of clips which provides a comparison between both encoding schemes. We provide options for evaluating not only different content and genres, but also the underlying encoding metrics, such as transmission cost, segment distribution (the range of the oscillation of the segment sizes) and associated delivery issues such as jitter and re-buffering. Finally, we also offer our datasets in a header-only compressed format, which allows researchers to download the entire dataset and uncompress locally, thus ensuring that our datasets are accessible both online via remote and local servers. en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher ACM en
dc.rights © Owner/Author ACM 2016. This is the author's version of the work. It is posted here for your personal use. Not for redistribution. The definitive Version of Record was published in Proceedings of the 7th International Conference on Multimedia Systems, http://dx.doi.org/10.1145/2910017.2910625 en
dc.subject AVC en
dc.subject HEVC en
dc.subject Dynamic Adaptive Streaming over HTTP en
dc.subject DASH en
dc.subject Dataset en
dc.title Datasets for AVC (H.264) and HEVC (H.265) evaluation of dynamic adaptive streaming over HTTP (DASH) en
dc.type Conference item en
dc.internal.authorcontactother Jason Quinlan, Computer Science, University College Cork, Cork, Ireland. +353-21-490-3000 Email: j.quinlan@cs.ucc.ie en
dc.internal.availability Full text available en
dc.description.version Accepted Version en
dc.internal.rssid 411920702
dc.contributor.funder Science Foundation Ireland en
dc.description.status Peer reviewed en
dc.identifier.journaltitle Proceedings of the 7th International Conference on Multimedia Systems en
dc.internal.copyrightchecked !!CORA!! en
dc.internal.conferencelocation Klagenfurt, Austria en
dc.internal.IRISemailaddress j.quinlan@cs.ucc.ie
dc.relation.project info:eu-repo/grantAgreement/SFI/SFI Investigator Programme/13/IA/1892/IE/An Internet Infrastructure for Video Streaming Optimisation (iVID)/ en


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