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dc.contributor.authorLi, Wenjie
dc.contributor.authorOteafy, Sharief M.A.
dc.contributor.authorFayed, Marwan
dc.contributor.authorHassanein, Hossam S.
dc.date.accessioned2020-11-19T10:30:09Z
dc.date.available2020-11-19T10:30:09Z
dc.date.issued2020-12-29
dc.identifier271276217
dc.identifiere56af966-235e-4204-b3c8-ef7542f91b5c
dc.identifier85099091253
dc.identifier000641964600006
dc.identifier.citationLi , W , Oteafy , S M A , Fayed , M & Hassanein , H S 2020 , ' Quality of experience in ICN : keep your low-bitrate close, and high-bitrate closer ' , IEEE/ACM Transactions on Networking , vol. Early access , pp. 1-14 . https://doi.org/10.1109/TNET.2020.3044995en
dc.identifier.issn1063-6692
dc.identifier.otherORCID: /0000-0002-0970-7972/work/86141125
dc.identifier.urihttps://hdl.handle.net/10023/21010
dc.description.abstractRecent studies into streaming media delivery suggest that performance gains from cache hierarchies such as Information-Centric Networks (ICNs) may be negated by Dynamic Adaptive Streaming (DAS), the de facto method for retrieving multimedia content. The bitrate adaptation mechanisms that drive video streaming clash with caching hierarchies in ways that affect users' Quality of Experience (QoE). Cache performance also diminishes as consumers dynamically select content encoded at different bitrates. In this paper we use the evidence to draw a novel insight: in a cache hierarchy for adaptive streaming content, bitrates should be prioritized over or alongside popularity and hit rates. We build on this insight to propose RippleCache as a family of cache placement schemes that safeguard high-bitrate content at the edge and push low-bitrate content into the network core. Doing so reduces contention of cache resources, as well as congestion in the network. To validate RippleCache claims we construct two separate implementations. We design RippleClassic as a benchmark solution that optimizes content placement by maximizing a measure for cache hierarchies shown to have high correlation with QoE. In addition, our lighter-weight RippleFinder is then re-designed with distributed execution for application in large-scale systems. RippleCache performance gains are reinforced by evaluations in NS-3 against state-of-the-art baseline approaches, using standard measures of QoE as defined by the DASH Industry Forum. Measurements show that RippleClassic and RippleFinder deliver content that suffers less oscillation and rebuffering, as well as the highest levels of video quality, indicating overall improvements to QoE.
dc.format.extent1116604
dc.language.isoeng
dc.relation.ispartofIEEE/ACM Transactions on Networkingen
dc.subjectInformation Centric Networken
dc.subjectNamed Data Networkingen
dc.subjectDynamic Adaptive Streamingen
dc.subjectIn-network cachingen
dc.subjectBitrate oscillationen
dc.subjectQA75 Electronic computers. Computer scienceen
dc.subjectT Technologyen
dc.subjectT-NDASen
dc.subjectBDCen
dc.subjectR2Cen
dc.subject~DC~en
dc.subject.lccQA75en
dc.subject.lccTen
dc.titleQuality of experience in ICN : keep your low-bitrate close, and high-bitrate closeren
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Computer Scienceen
dc.identifier.doihttps://doi.org/10.1109/TNET.2020.3044995
dc.description.statusPeer revieweden
dc.identifier.urlhttps://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=90en
dc.identifier.urlhttps://arxiv.org/abs/1903.09701en


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