Master data

Title: EMES: Efficient Multi-Encoding Schemes for HEVC-based Adaptive Bitrate Streaming
Subtitle:
Abstract:

In HTTP Adaptive Streaming  (HAS), videos are encoded at multiple bitrates and spatial resolutions ( i.e. , representations ) to adapt to the heterogeneity of network conditions, device attributes, and end-user preferences. Encoding the same video segment at multiple representations increases costs for content providers. State-of-the-art multi-encoding schemes improve the encoding process by utilizing encoder analysis information from already encoded representation(s) to reduce the encoding time of the remaining representations. These schemes typically use the highest bitrate representation as the reference to accelerate the encoding of the remaining representations. Nowadays, most streaming services utilize cloud-based encoding techniques, enabling a fully parallel encoding process to reduce the overall encoding time. The highest bitrate representation has the highest encoding time than the other representations. Thus, utilizing it as the reference encoding is unfavorable in a parallel encoding setup as the overall encoding time is bound by its encoding time. This paper provides a comprehensive study of various multi-rate and multi-encoding schemes in both serial and parallel encoding scenarios. Furthermore, it introduces novel heuristics to limit the Rate Distortion Optimization  (RDO) process across various representations. Based on these heuristics, three multi-encoding schemes are proposed, which rely on encoder analysis sharing across different representations: (i) optimized for the highest compression efficiency , (ii) optimized for the best compression efficiency-encoding time savings trade-off , and (iii) optimized for the best encoding time savings . Experimental results demonstrate that the proposed multi-encoding schemes (i) , (ii) , and (iii) reduce the overall serial encoding time by 34.71%, 45.27%, and 68.76% with a 2.3%, 3.1%, and 4.5% bitrate increase to maintain the same VMAF, respectively compared to stand-alone encodings. The overall parallel encoding time is reduced by 22.03%, 20.72%, and 76.82% compared to stand-alone encodings for schemes (i) , (ii) , and (iii) , respectively.

Keywords: HTTP Adaptive Streaming, HEVC, Multi-rate Encoding, Multi-encoding
Publication type: Article in journal (Authorship)
Publication date: 08.12.2022 (Online)
Published by: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM)
to publication
 ( ACM - New York; )
Title of the series: -
Volume number: -
Issue: -
First publication: Yes
Version: -
Page: pp. 1 - 20

Versionen

Keine Version vorhanden
Publication date: 12.2022
ISBN: -
ISSN: 1551-6857
Homepage: https://dl.acm.org/doi/10.1145/3575659
Publication date: 08.12.2022
ISBN (e-book): -
eISSN: 1551-6865
DOI: http://dx.doi.org/10.1145/3575659
Homepage: https://dl.acm.org/doi/10.1145/3575659
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
  • 1020 - Computer Sciences
Research Cluster No research Research Cluster selected
Citation index
  • Science Citation Index Expanded (SCI Expanded)
Information about the citation index: Master Journal List
Peer reviewed
  • Yes
Publication focus
  • Science to Science (Quality indicator: I)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Communication

Cooperations

No partner organisations selected

Articles of the publication

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