Edge Computing Assisted Adaptive Mobile Video Streaming
- Submitting institution
-
University of Northumbria at Newcastle
- Unit of assessment
- 11 - Computer Science and Informatics
- Output identifier
- 32130332
- Type
- D - Journal article
- DOI
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10.1109/TMC.2018.2850026
- Title of journal
- IEEE Transactions on Mobile Computing
- Article number
- -
- First page
- 787
- Volume
- 18
- Issue
- 4
- ISSN
- 1536-1233
- Open access status
- Deposit exception
- Month of publication
- June
- Year of publication
- 2018
- 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 - Cyber Security and Network Systems (CyberNets)
- Citation count
- 22
- Proposed double-weighted
- No
- Reserve for an output with double weighting
- No
- Additional information
- This research is significant because it proposes for the first time a network-assisted solution for DASH video streaming at large-scale which outperforms the current de-facto techniques. The outcome of this work has motivated partners from Aalto University, University of Helsinki, Ericsson, F-Secure and Datactica for the future development of its prototype. Supported by Nokia Center for Advanced Research, the results of this work were discussed in a meeting with the industrial partners and reported to Nokia Bell Labs. The outcome of this paper has further led to relevant discussion in CloSer & PraNA Joint Workshop in 2017 (https://www.cs.helsinki.fi/en/news/86556).
- Author contribution statement
- -
- Non-English
- No
- English abstract
- -