Stammdaten

Titel: Bandwidth prediction on low-latency chunked streaming
Untertitel:
Kurzfassung:

HTTP adaptive streaming with chunked transfer encoding can be used to offer low-latency streaming without sacrificing the coding efficiency. While this allows a media segment to be generated and delivered at the same time, which is critical in reducing the latency, the conventional bitrate adaptation schemes make often grossly inaccurate bandwidth measurements due to the presence of idle periods between the chunks. These wrong measurements cause the streaming client to make bad adaptation decisions. To this end, we design ACTE, a new bitrate adaptation scheme that leverages the unique nature of chunk downloads. ACTE uses a sliding window to accurately measure the available bandwidth and an online linear adaptive filter to predict the bandwidth into the future. Results show that ACTE achieves 96% measurement accuracy, which translates to a 65% reduction in the number of stalls and a 49% increase in quality of experience on average compared to other schemes.

Schlagworte: HAS; ABR; DASH; CMAF; low-latency; HTTP chunked transfer encoding; bandwidth measurement and prediction; RLS.
Publikationstyp: Beitrag in Proceedings (Autorenschaft)
Erscheinungsdatum: 21.06.2019 (Online)
Erschienen in: Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
Proceedings of the 29th ACM Workshop on Network and Operating Systems Support for Digital Audio and Video
zur Publikation
 ( ACM New York; )
Titel der Serie: -
Bandnummer: -
Erstveröffentlichung: Ja
Version: -
Seite: S. 7 - 13

Versionen

Keine Version vorhanden
Erscheinungsdatum: 21.06.2019
ISBN (e-book):
  • 978-1-4503-6298-6
eISSN: -
DOI: http://dx.doi.org/10.1145/3304112.3325611
Homepage: https://dl.acm.org/citation.cfm?doid=3304112.3325611
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
  • 202022 - Informationstechnik
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
Özyegin University
Nişantepe District, Orman Street
34794 Çekmeköy/Istanbul
Türkei
https://www.ozyegin.edu.tr/en/
Nişantepe District, Orman Street
TR - 34794  Çekmeköy/Istanbul

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