DASH QoE performance evaluation framework with 5G datasets

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dc.contributor.authorUl Mustafa, Raza
dc.contributor.authorIslam, Md. Tariqul
dc.contributor.authorRothenberg, Christian E.
dc.contributor.authorFerlin, Simone
dc.contributor.authorRaca, Darijo
dc.contributor.authorQuinlan, Jason J.
dc.date.accessioned2020-10-21T10:30:57Z
dc.date.available2020-10-21T10:30:57Z
dc.date.issued2020-11-02
dc.description.abstractFifth Generation (5G) networks provide high throughput and low delay, contributing to enhanced Quality of Experience (QoE) expectations. The exponential growth of multimedia traffic pose dichotomic challenges to simultaneously satisfy network operators, service providers, and end-user expectations. Building QoE-aware networks that provide run-time mechanisms to satisfy end-users’ expectations while the end-to end network Quality of Service (QoS) varies is challenging and motivates many ongoing research efforts. The contribution of this work is twofold. Firstly, we present a reproducible data-driven framework with a series of pre-installed Dynamic Adaptive Streaming over HTTP (DASH) tools to analyse state of-art Adaptive Bitrate Streaming (ABS) algorithms by varying key QoS parameters in static and mobility scenarios. Secondly, we introduce an interactive Binder notebook providing a live analytical environment which processes the output dataset of the framework and compares the relationship of five QoE models, three QoS parameters (RTT, throughput, packets), and seven video KPIs.en
dc.description.statusPeer revieweden
dc.description.versionAccepted Versionen
dc.format.mimetypeapplication/pdfen
dc.identifier.citationUl Mustafa, R., Islam,M. T., Rothenberg, C. E., Ferlin, S., Raca, D. and Quinlan, J. J. (2020) ‘DASH QoE Performance Evaluation Framework with 5G Datasets’, 2020 16th International Conference on Network and Service Management (CNSM), Izmir, Turkey [online], 2-6 Nov. doi: 10.23919/CNSM50824.2020.9269111en
dc.identifier.doi10.23919/CNSM50824.2020.9269111
dc.identifier.eissn2165-963X
dc.identifier.endpage6en
dc.identifier.isbn978-3-903176-31-7
dc.identifier.startpage1en
dc.identifier.urihttps://hdl.handle.net/10468/10672
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.relation.urihttps://ieeexplore.ieee.org/document/9269111
dc.rights© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other worksen
dc.subject5Gen
dc.subjectQoEen
dc.subjectQuality of Experience (QoE)en
dc.subjectQuality of Service (QoS)en
dc.subjectQoSen
dc.subjectABS algorithmen
dc.subjectAdaptive Bitrate Streaming (ABS)en
dc.subjectDASHen
dc.subjectDynamic Adaptive Streaming over HTTP (DASHen
dc.titleDASH QoE performance evaluation framework with 5G datasetsen
dc.typeConference itemen
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