Master data

Title: CADLAD: Device-aware Bitrate Ladder Construction for HTTP Adaptive Streaming
Subtitle:
Abstract:

In this paper, we introduce a CMCD-Aware per-Device bitrate LADder construction (CADLAD) that leverages the Common Media Client Data (CMCD) standard to address the above issues. CADLAD comprises components at both client and server sides. The client calculates the top bitrate (tb) — a CMCD parameter to indicate the highest bitrate that can be rendered at the client — and sends it to the server together with its device type and screen resolution. The server decides on a suitable bitrate ladder, whose maximum bitrate and resolution are based on CMCD parameters, to the client device with the purpose of providing maximum QoE while minimizing delivered data. CADLAD has two versions to work in Video on Demand (VoD) and live streaming scenarios. Our CADLAD is client agnostic; hence, it can work with any players and ABR algorithms at the client. The experimental results show that CADLAD is able to increase the QoE by 2.6x while saving 71% of delivered data, compared to an existing bitrate ladder of an available video dataset. We implement our idea within CAdViSE — an open-source testbed for reproducibility.

Keywords: HTTP Adaptive Streaming, QoE, live streaming, CMCD, bitrate ladder construction
Publication type: Article in Proceedings (Authorship)
Publication date: 31.10.2022 (Print)
Published by: CNSM'22 Proceedings of the 18th International Conference on Network and Service Management
CNSM'22 Proceedings of the 18th International Conference on Network and Service Management
to publication
 ( IEEE Xplore Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 198 - 204

Versionen

Keine Version vorhanden
Publication date: 31.10.2022
ISBN:
  • 978-3-903176-51-5
ISSN: -
Homepage: https://ieeexplore.ieee.org/document/9964669
Publication date: 02.12.2022
ISBN (e-book): -
eISSN: 2165-963X
DOI: http://dx.doi.org/10.23919/cnsm55787.2022.9964669
Homepage: https://ieeexplore.ieee.org/document/9964669
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
National University of Singapore
21 Lower Kent Ridge Rd
119077 Singapur
Singapore
21 Lower Kent Ridge Rd
SG - 119077  Singapur

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