Master data

Title: Bandwidth prediction on low-latency chunked streaming
Subtitle:
Abstract:

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.

Keywords: HAS; ABR; DASH; CMAF; low-latency; HTTP chunked transfer encoding; bandwidth measurement and prediction; RLS.
Publication type: Article in Proceedings (Authorship)
Publication date: 21.06.2019 (Online)
Published by: 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
to publication
 ( ACM New York; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 7 - 13

Versionen

Keine Version vorhanden
Publication date: 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
  • Available online (open access)

Assignment

Organisation Address
Fakultät für Technische Wissenschaften
 
Institut für Informationstechnologie
Universitaetsstr. 65-67
9020 Klagenfurt am Wörthersee
Austria
   martina.steinbacher@aau.at
http://itec.aau.at/
To organisation
Universitaetsstr. 65-67
AT - 9020  Klagenfurt am Wörthersee

Categorisation

Subject areas
  • 202022 - Information technology
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

Organisation Address
National University of Singapore
21 Lower Kent Ridge Rd
119077 Singapur
Singapore
21 Lower Kent Ridge Rd
SG - 119077  Singapur
Özyegin University
Nişantepe District, Orman Street
34794 Çekmeköy/Istanbul
Türkiye
https://www.ozyegin.edu.tr/en/
Nişantepe District, Orman Street
TR - 34794  Çekmeköy/Istanbul

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