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Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter

文献类型：期刊论文

作者Yu, Encheng5,6; Zhou, Jianer6; Li, Zhenyu1; Tyson, Gareth3; Li, Weicho6; Zhang, Xinyi2; Xu, Zhiwei4; Xie, Gaogang2
刊名ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS
出版日期2024-09-01
卷号20期号:9页码:23
关键词Information systems Multimedia streaming Networks Transport protocols Transport protocols
ISSN号1551-6857
DOI10.1145/3672399
英文摘要The advent of 5G and interactive live broadcasting has led to a growing trend of people preferring realtime interactive video services on mobile devices, particularly mobile phones. In this work, we measure the performance of Google congestion control (GCC) in cellular networks, which is the default congestion control algorithm for Web Real-Time Communication (WebRTC). Our measurements show that GCC sometimes makes bitrate decisions which are harmful to quality of experience (QoE) in cellular networks with high jitter. We further find that the frame delivery time (FDT) in the player can mitigate network jitter and maintain QoE. Moreover, the receiving rate is better to reflect the network congestion than RTT in cellular networks. Based on these measurements and findings, we propose Mustang, an algorithm designed to overcome the jitter in cellular networks. Mustang makes use of the FDT and receiving rate as feedback information to the sender. Then the sender adjusts its sending rate based on the information to guarantee QoE. We have implemented Mustang in WebRTC and evaluated it in both emulated and real cellular networks. The experimental results show that Mustang can improve WebRTC's QoS and QoE performance. For QoS, Mustang increases the sending rate by 72.1% and has similar RTT and packet loss when compared with GCC, while it is about 30% better for QoE.
资助项目Major Key Project of PCL[PCL2023AS1-5] ; Major Key Project of PCL[PCL2023AS1-3] ; Young Scientists Fund of the National Natural Science Foundation of China[62202447]
WOS研究方向Computer Science
语种英语
WOS记录号WOS:001325878000002
出版者ASSOC COMPUTING MACHINERY
源URL[http://119.78.100.204/handle/2XEOYT63/39551]  
专题中国科学院计算技术研究所期刊论文_英文
通讯作者Yu, Encheng
作者单位1.Chinese Acad Sci, ICT, Beijing, Peoples R China
2.Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China
3.Hong Kong Univ Sci & Technol, Guangzhou, Peoples R China
4.Haihe Lab Informat Technol & Applicat Innovat, Tianjin, Peoples R China
5.Southern Univ Sci & Technol, Shenzhen, Peoples R China
6.Peng Cheng Lab, Shenzhen, Peoples R China
推荐引用方式
GB/T 7714		 Yu, Encheng,Zhou, Jianer,Li, Zhenyu,et al. Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter[J]. ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,2024,20(9):23.
APA Yu, Encheng.,Zhou, Jianer.,Li, Zhenyu.,Tyson, Gareth.,Li, Weicho.,...&Xie, Gaogang.(2024).Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter.ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS,20(9),23.
MLA Yu, Encheng,et al."Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter".ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 20.9(2024):23.

入库方式： OAI收割

来源：计算技术研究所

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