中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
首页 机构 成果 学者
  
  1. CAS IR Grid
  2. 计算技术研究所
  3. 中国科学院计算技术研究所
  4. 中国科学院计算技术研究所期刊论文
  5. 英文
Accurate Throughput Prediction for Improving QoE in Mobile Adaptive Streaming

文献类型：期刊论文

作者Lv, Gerui1,2; Wu, Qinghua1,2,3; Tan, Qingyue1,2; Wang, Weiran1,2; Li, Zhenyu1,2,3; Xie, Gaogang2,4
刊名IEEE TRANSACTIONS ON MOBILE COMPUTING
出版日期2024-05-01
卷号23期号:5页码:5799-5817
关键词Adaptive streaming mobile internet QoE improvement throughput prediction
ISSN号1536-1233
DOI10.1109/TMC.2023.3313592
英文摘要Video streaming is the most important mobile application today. To improve users' quality of experience (QoE), the client player runs adaptive bitrate (ABR) algorithms that dynamically select the bitrate for video chunks based on throughput or delivery time predictions. This paper aims to design an accurate predictor for mobile adaptive streaming by investigating all its components, including input features, output target, and mapping function. We construct the first theoretical framework that reveals potential factors affecting chunk throughput and delivery time. To verify this framework, we provide formulation analysis and measurement observations based on 2500+ video sessions collected in real-world mobile networks. We find that previous works have failed to achieve accurate prediction due to overlooking the impact of the transport mechanism and application behavior on throughput. Furthermore, we show that throughput is a better target for data-driven predictors than delivery time, due to the long-tailed distribution of delivery time. Based on the above, we propose Lumos, a decision-tree-based throughput predictor that can be integrated into various ABR algorithms. Extensive experiments in real-world mobile Internet show that Lumos achieves high prediction accuracy and improves the QoE of MPC by 6.3%, and MPC+Lumos outperforms Pensieve by 19.2%.
资助项目National Key R#x0026;D Program of China
WOS研究方向Computer Science ; Telecommunications
语种英语
WOS记录号WOS:001198016900056
出版者IEEE COMPUTER SOC
源URL[http://119.78.100.204/handle/2XEOYT63/39687]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Xie, Gaogang
作者单位1.Chinese Acad Sci, Inst Comp Technol, Beijing 101408, Peoples R China
2.Univ Chinese Acad Sci, Beijing 101408, Peoples R China
3.Purple Mt Labs, Nanjing 211100, Peoples R China
4.Chinese Acad Sci, Comp Network Informat Ctr, Beijing 101408, Peoples R China
推荐引用方式
GB/T 7714		 Lv, Gerui,Wu, Qinghua,Tan, Qingyue,et al. Accurate Throughput Prediction for Improving QoE in Mobile Adaptive Streaming[J]. IEEE TRANSACTIONS ON MOBILE COMPUTING,2024,23(5):5799-5817.
APA Lv, Gerui,Wu, Qinghua,Tan, Qingyue,Wang, Weiran,Li, Zhenyu,&Xie, Gaogang.(2024).Accurate Throughput Prediction for Improving QoE in Mobile Adaptive Streaming.IEEE TRANSACTIONS ON MOBILE COMPUTING,23(5),5799-5817.
MLA Lv, Gerui,et al."Accurate Throughput Prediction for Improving QoE in Mobile Adaptive Streaming".IEEE TRANSACTIONS ON MOBILE COMPUTING 23.5(2024):5799-5817.

入库方式： OAI收割

来源：计算技术研究所

浏览0
下载0
收藏0
其他版本

除非特别说明，本系统中所有内容都受版权保护，并保留所有权利。