Master data

Title: Context-Aware HTTP Adaptive Video Streaming Utilizing QUIC's Stream Priority
Subtitle:
Abstract:

In recent years, HTTP Adaptive Streaming (HAS) has been a predominant video delivery technology over the Internet. The existing HAS-based techniques ignore the context and the affective content of the video, rather its prime focus relies on determining the video quality of the fore coming data based on the current network conditions [4, 5]. By highlighting the video traffic based on the context (e.g., the goal in a soccer match or the climax of a movie) and allocating more network resources (e.g., prioritizing the important segments) to the highlighted segments will lead to end user satisfaction with a pleasant Quality of Experience (QoE). Quick UDP Internet Connections (QUIC), a recently standardized transport protocol, has gained popularity due to its promising features, e.g., reduced connection establishment latency, stream multiplexing and stream priority. This paper leverages QUIC's stream priority to support context-based streaming by introducing a novel video delivery approach.

Keywords: HTTP Adaptive Streaming (HAS), QUIC, Context-aware Delivery
Publication type: Article in Proceedings (Authorship)
Publication date: 07.05.2023 (Print)
Published by: MHV'23 Proceedings of the 2nd ACM Mile-High Video Conference 2023
MHV'23 Proceedings of the 2nd ACM Mile-High Video Conference 2023
to publication
 ( ACM Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 144 - 145

Versionen

Keine Version vorhanden
Publication date: 07.05.2023
ISBN:
  • 979-8-4007-0160-3
ISSN: -
Homepage: https://dl.acm.org/doi/10.1145/3588444.3591038
Publication date: 16.06.2023
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1145/3588444.3591038
Homepage: https://dl.acm.org/doi/10.1145/3588444.3591038
Open access
  • Available online (not 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
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: II)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

Organisation Address
University of New Hampshire
Durham
United States of America
US  Durham

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