南方科技大学知识苑(SUSTech KC): Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter

题名	Mustang: Improving QoE for Real-Time Video in Cellular Networks by Masking Jitter
作者	Yu, Encheng1,2 ; Zhou, Jianer 2; Li, Zhenyu 3; Tyson, Gareth 4; Li, Weicho 2; Zhang, Xinyi 5; Xu, Zhiwei 6; Xie, Gaogang 5
通讯作者	Yu, Encheng
发表日期	2024-09-01
DOI	10.1145/3672399
发表期刊	ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 影响因子和分区
ISSN	1551-6857
EISSN	1551-6865
卷号	20 期号:9
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.
关键词	Information systems Multimedia streaming Networks Transport protocols Transport protocols
相关链接	[来源记录]
收录类别	SCI
语种	英语
学校署名	第一 ; 通讯
资助项目	Major Key Project of PCL["PCL2023AS1-5","PCL2023AS1-3"] ; Young Scientists Fund of the National Natural Science Foundation of China[62202447]
WOS研究方向	Computer Science
WOS类目	Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
WOS记录号	WOS:001325878000002
出版者	ASSOC COMPUTING MACHINERY
来源库	Web of Science
引用统计
成果类型	期刊论文
条目标识符	http://sustech.caswiz.com/handle/2SGJ60CL/842834
专题	南方科技大学
作者单位	1.Southern Univ Sci & Technol, Shenzhen, Peoples R China 2.Peng Cheng Lab, Shenzhen, Peoples R China 3.Chinese Acad Sci, ICT, Beijing, Peoples R China 4.Hong Kong Univ Sci & Technol, Guangzhou, Peoples R China 5.Chinese Acad Sci, Comp Network Informat Ctr, Beijing, Peoples R China 6.Haihe Lab Informat Technol & Applicat Innovat, Tianjin, Peoples R China
第一作者单位	南方科技大学
通讯作者单位	南方科技大学
第一作者的第一单位	南方科技大学
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).
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).
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).