Master data

Title: Towards Better Quality of Experience in HTTP Adaptive Streaming
Subtitle:
Abstract:

HTTP Adaptive Streaming (HAS) is nowadays a popular solution for multimedia delivery. The novelty of HAS lies in the possibility of continuously adapting the streaming session to current network conditions, facilitated by Adaptive Bitrate (ABR) algorithms. Various popular streaming and Video on Demand services such as Netflix, Amazon Prime Video, and Twitch use this method. Given this broad consumer base, ABR algorithms continuously improve to increase user satisfaction. The insights for these improvements are, among others, gathered within the research area of Quality of Experience (QoE). Within this field, various researchers have dedicated their works to identifying potential impairments and testing their impact on viewers’ QoE. Two frequently discussed visual impairments influencing QoE are stalling events and quality switches. So far, it is commonly assumed that those stalling events have the worst impact on QoE. This paper challenged this belief and reviewed this assumption by comparing stalling events with multiple quality and high amplitude quality switches. Two subjective studies were conducted. During the first subjective study, participants received a monetary incentive, while the second subjective study was carried out with volunteers. The statistical analysis demonstrated that stalling events do not result in the worst degradation of QoE. These findings suggest that a reevaluation of the effect of stalling events in QoE research is needed. Therefore, these findings may be used for further research and to improve current adaptation strategies in ABR algorithms.

Keywords: HTTP Adaptive Streaming, Quality of Experience, Subjective Evaluation, Crowdsourcing
Publication type: Article in Proceedings (Authorship)
Publication date: 10.2022 (Print)
Published by: SITIS 2022 Proceedings of the 16th International Conference on Signal-Image Technology and Internet-Based Systems
SITIS 2022 Proceedings of the 16th International Conference on Signal-Image Technology and Internet-Based Systems
to publication
 ( IEEE Xplore Digital Library; )
Title of the series: -
Volume number: -
First publication: Yes
Version: -
Page: pp. 608 - 615

Versionen

Keine Version vorhanden
Publication date: 10.2022
ISBN:
  • 978-1-6654-6495-6
ISSN: -
Homepage: https://ieeexplore.ieee.org/document/10090100
Publication date: 10.04.2023
ISBN (e-book): -
eISSN: -
DOI: http://dx.doi.org/10.1109/sitis57111.2022.00096
Homepage: https://ieeexplore.ieee.org/document/10090100
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: III)
Classification raster of the assigned organisational units:
working groups
  • Multimedia Systeme

Cooperations

No partner organisations selected

Articles of the publication

No related publications