Advanced search
2 files | 8.67 MB

Quality of experience-centric management of adaptive video streaming services : status and challenges

Stefano Petrangeli (UGent) , Jeroen van der Hooft (UGent) , Tim Wauters (UGent) and Filip De Turck (UGent)
Author
Organization
Abstract
Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years.
Keywords
HTTP, OPTIMIZATION, PERFORMANCE, NETWORKS, FRAMEWORK, DELIVERY, INTERNET, STANDARD, DASH, SDN, Quality of experience, HTTP adaptive streaming, MPEG-DASH

Downloads

  • (...).pdf
    • full text
    • |
    • UGent only
    • |
    • PDF
    • |
    • 2.68 MB
  • 7230 i.pdf
    • full text
    • |
    • open access
    • |
    • PDF
    • |
    • 6.00 MB

Citation

Please use this url to cite or link to this publication:

Chicago
Petrangeli, Stefano, Jeroen van der Hooft, Tim Wauters, and Filip De Turck. 2018. “Quality of Experience-centric Management of Adaptive Video Streaming Services : Status and Challenges.” Acm Transactions on Multimedia Computing Communications and Applications 14 (2).
APA
Petrangeli, S., van der Hooft, J., Wauters, T., & De Turck, F. (2018). Quality of experience-centric management of adaptive video streaming services : status and challenges. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS, 14(2).
Vancouver
1.
Petrangeli S, van der Hooft J, Wauters T, De Turck F. Quality of experience-centric management of adaptive video streaming services : status and challenges. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS. New york: Assoc Computing Machinery; 2018;14(2).
MLA
Petrangeli, Stefano, Jeroen van der Hooft, Tim Wauters, et al. “Quality of Experience-centric Management of Adaptive Video Streaming Services : Status and Challenges.” ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 14.2 (2018): n. pag. Print.
@article{8567108,
  abstract     = {Video streaming applications currently dominate Internet traffic. Particularly, HTTP Adaptive Streaming ( HAS) has emerged as the dominant standard for streaming videos over the best-effort Internet, thanks to its capability of matching the video quality to the available network resources. In HAS, the video client is equipped with a heuristic that dynamically decides the most suitable quality to stream the content, based on information such as the perceived network bandwidth or the video player buffer status. The goal of this heuristic is to optimize the quality as perceived by the user, the so-called Quality of Experience (QoE). Despite the many advantages brought by the adaptive streaming principle, optimizing users' QoE is far from trivial. Current heuristics are still suboptimal when sudden bandwidth drops occur, especially in wireless environments, thus leading to freezes in the video playout, the main factor influencing users' QoE. This issue is aggravated in case of live events, where the player buffer has to be kept as small as possible in order to reduce the playout delay between the user and the live signal. In light of the above, in recent years, several works have been proposed with the aim of extending the classical purely client-based structure of adaptive video streaming, in order to fully optimize users' QoE. In this article, a survey is presented of research works on this topic together with a classification based on where the optimization takes place. This classification goes beyond client-based heuristics to investigate the usage of server-and network-assisted architectures and of new application and transport layer protocols. In addition, we outline the major challenges currently arising in the field of multimedia delivery, which are going to be of extreme relevance in future years.},
  articleno    = {31},
  author       = {Petrangeli, Stefano and van der Hooft, Jeroen and Wauters, Tim and De Turck, Filip},
  issn         = {1551-6857},
  journal      = {ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS},
  keywords     = {HTTP,OPTIMIZATION,PERFORMANCE,NETWORKS,FRAMEWORK,DELIVERY,INTERNET,STANDARD,DASH,SDN,Quality of experience,HTTP adaptive streaming,MPEG-DASH},
  language     = {eng},
  number       = {2},
  pages        = {29},
  publisher    = {Assoc Computing Machinery},
  title        = {Quality of experience-centric management of adaptive video streaming services : status and challenges},
  url          = {http://dx.doi.org/10.1145/3165266},
  volume       = {14},
  year         = {2018},
}

Altmetric
View in Altmetric
Web of Science
Times cited: