GCC-beta: Improving Interactive Live Video Streaming via an Adaptive Low-Latency Congestion Control
Leilei Wu, Anfu Zhou, Xiaojiang Chen, Liang Liu, Huadóng Ma · 2019
Google congestion control (GCC) is the de-facto standard for web real-time communications (WebRTC) applications and has been implemented in mainstream browsers including Chrome and Firefox. While GCC is designed to achieve high video bit-rate and low latency simultaneously, we find that GCC's performance is far from satisfactory particularly under good network conditions. In particular, we collect a GCC trace dataset with over 1.18 million sessions from a major crowd-sourced live video streaming service provider. We perform in-depth analytics using the dataset, which shows that the sending video bit-rate unnecessarily experiences frequent rollbacks caused by minor fluctuation of transmission delay. To address the issue, we propose a mechanism called GCC-β, which can distinguish normal network fluctuation from real network congestion, and then adaptively sends appropriate bitrates. We implement GCC-β in the WebRTC framework and evaluate its performance using test-bed experiments. The results show that GCC-β is able to avoid up to 90% unnecessary bitrate rollbacks.