Stammdaten

Titel: Understanding quality of experience of heuristic-based HTTP adaptive bitrate algorithms
Untertitel:
Kurzfassung:

Adaptive bitrate (ABR) algorithms play a crucial role in delivering the highest possible viewer's Quality of Experience (QoE) in HTTP Adaptive Streaming (HAS). Online video streaming service providers use HAS - the dominant video streaming technique on the Internet - to deliver the best QoE for their users. A viewer's delight relies heavily on how the ABR of a media player can adapt the stream's quality to the current network conditions. QoE for video streaming sessions has been assessed in many research projects to give better insight into the significant quality metrics such as startup delay and stall events. The ITU Telecommunication Standardization Sector (ITU-T) P.1203 quality evaluation model allows to algorithmically predict a subjective Mean Opinion Score (MOS) by considering various quality metrics. Subjective evaluation is the best assessment method for examining the end-user opinion over a video streaming session's experienced quality. We have conducted subjective evaluations with crowdsourced participants and evaluated the MOS of the sessions using the ITU-T P.1203 quality model. This paper's main contribution is to investigate the correspondence of subjective and objective evaluations for well-known heuristic-based ABRs.

Schlagworte: HTTP Adaptive Streaming, ABR Algorithms, Quality of Experience, Crowdsourcing, Subjective Evaluation, Objective Evaluation, MOS
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Art der Veröffentlichung Online Publikation
Erschienen in: Nossdav '21: Proceedings of the 31st ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
Nossdav '21: Proceedings of the 31st ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
zur Publikation
 ( ACM Digital Library; )
Erscheinungsdatum: 16.07.2021
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 82 - 89

Identifikatoren

ISBN:
  • 9781450384353
ISSN: -
DOI: http://dx.doi.org/10.1145/3458306.3458875
AC-Nummer: -
Homepage: https://dl.acm.org/doi/10.1145/3458306.3458875
Open Access
  • Online verfügbar (Open Access)

Zuordnung

Organisation Adresse
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Österreich
   martina.steinbacher@aau.at
http://itec.aau.at/
zur Organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Kategorisierung

Sachgebiete
  • 1020 - Informatik
Forschungscluster Kein Forschungscluster ausgewählt
Peer Reviewed
  • Ja
Publikationsfokus
  • Science to Science (Qualitätsindikator: I)
Klassifikationsraster der zugeordneten Organisationseinheiten:
Arbeitsgruppen
  • Multimedia Communication

Kooperationen

Organisation Adresse
National University of Singapore
21 Lower Kent Ridge Rd
119077 Singapur
Singapur
21 Lower Kent Ridge Rd
SG - 119077  Singapur

Beiträge der Publikation

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