RAV: Learning-Based Adaptive Streaming to Coordinate the Audio and Video Bitrate Selections
RAV: Learning-Based Adaptive Streaming to Coordinate the Audio and Video Bitrate Selections
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RAV：基于学习的自适应流媒体来协调音频和视频比特率选择
DOI：
10.1109/tmm.2022.3198013
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发表时间：
2023
影响因子：
7.3
通讯作者：
Jianxin Wang
中科院分区：
文献类型：
--
作者：
Weihe Li;Jiawei Huang;Wenjun Lyu;Baoshen Guo;Wanchun Jiang;Jianxin Wang
Most commercial players adopt adaptive bitrate (ABR) algorithms to dynamically decide each chunk's bitrate based on the perceived network bandwidth and buffer occupancy. However, current ABR algorithms are agnostic of audio bitrate selection since they deem it has negligible influence on video bitrate selection due to small size of audio chunks. Nevertheless, with the development of audio technologies, the bitrate of audio content increases dramatically in recent years. Thus, inappropriate audio selection can significantly affect video selection and deteriorate the viewing experience. To tackle these inefficiencies, we propose a deep Reinforcement learning-based ABR algorithm that takes Audio and Video quality into account (RAV) to circumvent a series of suboptimal performances, like low playback quality, frequent playback interruptions, poor playback smoothness, and undesirable combinations of video and audio chunks. Furthermore, RAV trains a neural network model that automatically outputs the bitrates for future audio and video chunks without relying on any presumptions about the environment, achieving good robustness to a broad spectrum of conditions. By conducting trace-driven and real-world experiments, we demonstrate that RAV significantly ameliorates the average overall viewing quality by 37.96%-118.20% over the state-of-the-art ABR algorithms. In addition, we also conduct subjective experiments by inviting 32 volunteers, and 27/32 users strongly agree that RAV provides them a better viewing experience than existing ABR solutions.
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DOI：
10.1109/infocom41043.2020.9155411
发表时间：
2020-07
期刊：
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
影响因子：
--
作者：
Tianchi Huang;Chao Zhou;Ruixiao Zhang;Chenglei Wu;Xin Yao;Lifeng Sun
通讯作者：
Tianchi Huang;Chao Zhou;Ruixiao Zhang;Chenglei Wu;Xin Yao;Lifeng Sun
DOI：
10.1109/infocom.2016.7524428
发表时间：
2016-01
期刊：
IEEE INFOCOM 2016 - The 35th Annual IEEE International Conference on Computer Communications
影响因子：
--
作者：
Kevin Spiteri;Rahul Urgaonkar;R. Sitaraman
通讯作者：
Kevin Spiteri;Rahul Urgaonkar;R. Sitaraman
DOI：
10.1109/globecom42002.2020.9322459
发表时间：
2020-12
期刊：
GLOBECOM 2020 - 2020 IEEE Global Communications Conference
影响因子：
--
作者：
Weihe Li;Jiawei Huang;Shiqi Wang-;Sen Liu;Jianxin Wang
通讯作者：
Weihe Li;Jiawei Huang;Shiqi Wang-;Sen Liu;Jianxin Wang
影响因子：
3.7
作者：
Jiang, Junchen;Sekar, Vyas;Zhang, Hui
通讯作者：
Zhang, Hui
DOI：
10.1109/infocom41043.2020.9155492
发表时间：
2020-07
期刊：
IEEE INFOCOM 2020 - IEEE Conference on Computer Communications
影响因子：
--
作者：
Yushuo Guan;Yuanxing Zhang;Bingxuan Wang;Kaigui Bian;Xiaoliang Xiong;Lingyang Song
通讯作者：
Yushuo Guan;Yuanxing Zhang;Bingxuan Wang;Kaigui Bian;Xiaoliang Xiong;Lingyang Song