A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos
Time delay and image quality degradation are main challenges faced by streaming video transmission. How to make adaptive planning for transmission schemes according to dynamic change of transmission environment, always remains a technical concern. As a consequence, this paper proposes a deep reinfor...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10494754/ |
| _version_ | 1797201360509206528 |
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| author | Yawen Yang Yuxuan Xiao |
| author_facet | Yawen Yang Yuxuan Xiao |
| author_sort | Yawen Yang |
| collection | DOAJ |
| description | Time delay and image quality degradation are main challenges faced by streaming video transmission. How to make adaptive planning for transmission schemes according to dynamic change of transmission environment, always remains a technical concern. As a consequence, this paper proposes a deep reinforcement learning-based optimal transmission control method for streaming videos. Firstly, edge buffer task allocation is combined with quality of experience (QoE)-oriented deep reinforcement learning algorithm, in order to develop a resource allocation method for streaming videos. Secondly, an actively coordinated streaming data streaming transmission mechanism is established to construct a specific optimal transmission control method that satisfies environment requirement. Finally, a set of experiments are conducted to verify effectiveness and performance on public video transmission datasets. And the proposal is compared with several traditional transmission methods. The experiments show that the proposal in this work can effectively reduce delay and startup time and improve the QoE. This shows that the proposal is able to bring better stability and transmission quality. |
| first_indexed | 2024-04-24T07:46:18Z |
| format | Article |
| id | doaj.art-f39d32fed92c4ef8b0129109c1edf0d7 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-24T07:46:18Z |
| publishDate | 2024-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-f39d32fed92c4ef8b0129109c1edf0d72024-04-18T23:00:49ZengIEEEIEEE Access2169-35362024-01-0112530885309810.1109/ACCESS.2024.338617610494754A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming VideosYawen Yang0Yuxuan Xiao1https://orcid.org/0009-0007-0073-6404College of Humanities and Arts, Hunan International Economics University, Changsha, ChinaCollege of Design Arts, Changsha University of Science and Technology, Changsha, ChinaTime delay and image quality degradation are main challenges faced by streaming video transmission. How to make adaptive planning for transmission schemes according to dynamic change of transmission environment, always remains a technical concern. As a consequence, this paper proposes a deep reinforcement learning-based optimal transmission control method for streaming videos. Firstly, edge buffer task allocation is combined with quality of experience (QoE)-oriented deep reinforcement learning algorithm, in order to develop a resource allocation method for streaming videos. Secondly, an actively coordinated streaming data streaming transmission mechanism is established to construct a specific optimal transmission control method that satisfies environment requirement. Finally, a set of experiments are conducted to verify effectiveness and performance on public video transmission datasets. And the proposal is compared with several traditional transmission methods. The experiments show that the proposal in this work can effectively reduce delay and startup time and improve the QoE. This shows that the proposal is able to bring better stability and transmission quality.https://ieeexplore.ieee.org/document/10494754/Deep reinforcement learningstreaming videosoptimal transmission controlquality of experience |
| spellingShingle | Yawen Yang Yuxuan Xiao A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos IEEE Access Deep reinforcement learning streaming videos optimal transmission control quality of experience |
| title | A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos |
| title_full | A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos |
| title_fullStr | A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos |
| title_full_unstemmed | A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos |
| title_short | A Deep Reinforcement Learning-Based Optimal Transmission Control Method for Streaming Videos |
| title_sort | deep reinforcement learning based optimal transmission control method for streaming videos |
| topic | Deep reinforcement learning streaming videos optimal transmission control quality of experience |
| url | https://ieeexplore.ieee.org/document/10494754/ |
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