Deep Reinforcement Learning-Based Collaborative Video Caching and Transcoding in Clustered and Intelligent Edge B5G Networks
Joint Authors
Source
Wireless Communications and Mobile Computing
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-16, 16 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-12
Country of Publication
Egypt
No. of Pages
16
Main Subjects
Information Technology and Computer Science
Abstract EN
In the next-generation wireless communications system of Beyond 5G networks, video streaming services have held a surprising proportion of the whole network traffic.
Furthermore, the user preference and demand towards a specific video might be different because of the heterogeneity of users’ processing capabilities and the variation of network condition.
Thus, it is a complicated decision problem with high-dimensional state spaces to choose appropriate quality videos according to users’ actual network condition.
To address this issue, in this paper, a Content Distribution Network and Cluster-based Mobile Edge Computing framework has been proposed to enhance the ability of caching and computing and promote the collaboration among edge severs.
Then, we develop a novel deep reinforcement learning-based framework to automatically obtain the intracluster collaborative caching and transcoding decisions, which are executed based on video popularity, user requirement prediction, and abilities of edge servers.
Simulation results demonstrate that the quality of video streaming service can be significantly improved by using the designed deep reinforcement learning-based algorithm with less backhaul consumption and processing costs.
American Psychological Association (APA)
Wan, Zheng& Li, Yan. 2020. Deep Reinforcement Learning-Based Collaborative Video Caching and Transcoding in Clustered and Intelligent Edge B5G Networks. Wireless Communications and Mobile Computing،Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1214490
Modern Language Association (MLA)
Wan, Zheng& Li, Yan. Deep Reinforcement Learning-Based Collaborative Video Caching and Transcoding in Clustered and Intelligent Edge B5G Networks. Wireless Communications and Mobile Computing No. 2020 (2020), pp.1-16.
https://search.emarefa.net/detail/BIM-1214490
American Medical Association (AMA)
Wan, Zheng& Li, Yan. Deep Reinforcement Learning-Based Collaborative Video Caching and Transcoding in Clustered and Intelligent Edge B5G Networks. Wireless Communications and Mobile Computing. 2020. Vol. 2020, no. 2020, pp.1-16.
https://search.emarefa.net/detail/BIM-1214490
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1214490