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Real-time video streaming relies on rate control mechanisms to adapt videobitrate to network capacity while maintaining high utilization and low delay.However, the current video rate controllers, such as Google Congestion Control(GCC) in WebRTC, are very slow to respond to network changes, leading to linkunder-utilization and latency spikes. While recent delay-based congestioncontrol algorithms promise high efficiency and rapid adaptation to variableconditions, low-latency video applications have been unable to adopt theseschemes due to the intertwined relationship between video encoders and ratecontrol in current systems.  This paper introduces Vidaptive, a new rate control mechanism designed forlow-latency video applications. Vidaptive decouples packet transmissiondecisions from encoder output, injecting dummy padding traffic as needed totreat video streams akin to backlogged flows controlled by a delay-basedcongestion controller. Vidaptive then adapts the frame rate, resolution, andtarget bitrate of the encoder to align the video bitrate with the congestioncontroller's sending rate. Our evaluations atop WebRTC show that, across a setof cellular traces, Vidaptive achieves ~2x higher video bitrate and 1.6 dBhigher PSNR, and it reduces 95th-percentile frame latency by 2.7s with a slightincrease in median frame latency.

Vidaptive: Efficient and Responsive Rate Control for Real-Time Video on Variable Networks