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

Authors :
Yu, Encheng
Zhou, Jianer
Li, Zhenyu
Tyson, Gareth
Li, Weichao
Zhang, Xinyi
Xu, Zhiwei
Xie, Gaogang
Source :
ACM Transactions on Multimedia Computing, Communications & Applications; Sep2024, Vol. 20 Issue 9, p1-23, 23p
Publication Year :
2024

Abstract

The advent of 5G and interactive live broadcasting has led to a growing trend of people preferring real-time 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. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
15516857
Volume :
20
Issue :
9
Database :
Complementary Index
Journal :
ACM Transactions on Multimedia Computing, Communications & Applications
Publication Type :
Academic Journal
Accession number :
179790516
Full Text :
https://doi.org/10.1145/3672399