期刊
IEEE SYSTEMS JOURNAL
卷 16, 期 2, 页码 3433-3436出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/JSYST.2022.3144218
关键词
Video recording; Quality assessment; Quality of service; Streaming media; Static VAr compensators; Optimization; Wireless sensor networks; Markov decision processes (MDPs); mean-variance optimization; QoS guarantee; scalable video coding (SVC); wireless video streaming
类别
资金
- Guangdong Pearl River Talent Recruitment Program [62073115]
- [2019ZT08X603]
This article addresses the provisioning of multiple statistical Quality of Service (QoS) for real-time scalable video streaming over wireless fading channels. It presents a traffic rate adaptation (TRA) strategy that delivers encoding layers selectively based on dynamic channel conditions, minimizing video quality variation while maintaining satisfactory average video quality. The QoS-guaranteed TRA policy optimization is formulated using Markov decision processes, and a vector-composed policy gradient algorithm is developed for online mean-variance optimization. Simulation results demonstrate the effectiveness of the presented strategy.
Provisioning multiple statistical QoS for real-time scalable video streaming over wireless fading channels is addressed in this article. A traffic rate adaptation (TRA) strategy is presented to minimize the video quality variation while keeping satisfactory average video quality by selectively delivering encoding layers of video streaming depending on dynamic channel conditions. The QoS-guaranteed TRA policy optimization is formulated based on Markov decision processes. A vector-composed policy gradient algorithm that combines gradient estimate and stochastic approximation is developed to solve the constrained mean-variance optimization problem online. It is attractive for online control and optimization with high computational efficiency and adaptability to unknown environments. Simulation results show the effectiveness of the presented strategy.
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