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Cao, Yue, Wang, Ning, Wu, Celimuge, Zhang, Xu 
ORCID: https://orcid.org/0000-0001-6557-6607 and Suthaputchakun, Chakkaphong
(2019)
Enhancing video QoE over high-speed train using segment-based prefetching and caching.
IEEE MultiMedia, 26 (4).
pp. 55-66.
ISSN 1070-986X
Abstract
The big picture of 5G will bring a range of new unique service capabilities, where ensuring Quality of Experience (QoE) continuity in challenging situations such as high mobility, e.g., on-board user equipments (UEs) in high-speed train (HST) are one of the sharp killer applications. In this paper, we propose a mobile edge computing (MEC) driven solution to improve the QoE for UEs in the HST with perceived dynamic adaptive streaming over HTTP video demands. Considering the challenging wireless communication conditioning (e.g., path loss and Doppler Effect due to high mobility) between HST and base station along the railway for enabling progress and seamless video consuming, the case study shows the benefit of MEC functions mainly from content prefetching and complementarily from content caching, over benchmark solution where UEs solely download video segments through challenging wireless channel.
| Item Type: | Article |
|---|---|
| Additional Information: | Publisher Copyright: © 1994-2012 IEEE. |
| Uncontrolled Keywords: | software,signal processing,media technology,hardware and architecture,computer science applications ,/dk/atira/pure/subjectarea/asjc/1700/1712 |
| Faculty \ School: | Faculty of Science > School of Computing Sciences |
| UEA Research Groups: | Faculty of Science > Research Groups > Data Science and AI |
| Related URLs: | |
| Depositing User: | LivePure Connector |
| Date Deposited: | 26 Jan 2024 02:15 |
| Last Modified: | 10 Dec 2024 01:43 |
| URI: | https://ueaeprints.uea.ac.uk/id/eprint/94264 |
| DOI: | 10.1109/MMUL.2019.2905531 |
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