On the trajectory of video quality transition in HTTP adaptive video streaming
- Submitting institution
-
The University of Lancaster
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 281143876
- Type
- D - Journal article
- DOI
-
10.1007/s00530-017-0554-9
- Title of journal
- Multimedia Systems
- Article number
- -
- First page
- 327
- Volume
- 24
- Issue
- 3
- ISSN
- 0942-4962
- Open access status
- Compliant
- Month of publication
- June
- Year of publication
- 2017
- URL
-
-
- Supplementary information
-
-
- Request cross-referral to
- -
- Output has been delayed by COVID-19
- No
- COVID-19 affected output statement
- -
- Forensic science
- No
- Criminology
- No
- Interdisciplinary
- No
- Number of additional authors
-
2
- Research group(s)
-
F - Networking
- Citation count
- 0
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This foundational work won the IEEE ICME Grand Challenge 2016 in the field of Dynamic Adaptive Streaming over HTTP. It has since been used externally by several researchers as a baseline for performance evaluation when developing a bio-inspired HTTP-based adaptive streaming player, and a managed video delivery framework. The work underpinned the application for a funded Science Foundation Ireland (SFI) Industrial fellowship (Grant ID 18/IF/6354, collaborators AT&T Labs Research and Dell EMC Corp). As part of the project the algorithms were incorporated into the ExoPlayer (Android media framework), dash.js (DASH Industry reference player), and the opensource testbed framework (DASHbed).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -
