Tackling Bit-Rate Variation of RTC Through Frame-Bursting Congestion Control

Zhidong Jia, Yihang Zhang, Qingyang Li, Xinggong Zhang

Abstract: Interactive video applications signal widespread interest in Real-time communication (RTC), yet issues like frame delay, rebuffering, etc. remain a common complaint. We argue that this is mainly due to legacy network-oriented congestion control (CC), which assumes a continuous stream of packets is being sent. But this assumption doesn't hold in RTC since the video encoder exhibits inherent bit-rate variation: (1) Bursty spiking bit-rate leads to packets waiting in the sending buffer, which increases frame delay. (2) Low bit-rate causes insufficient packets available for sending, making current CCs hard to detect available bandwidth. In response, we propose BurstRTC, a novel paradigm for RTC transport protocol. Each frame is emitted as a whole, and the video bit-rate is directly controlled by network congestion feedback. BurstRTC uses frame-bursting to estimate available bandwidth efficiently regardless of bit-rate variation. Considering the impact of bit-rate variation on network congestion, BurstRTC models frame size as a Gaussian distribution instead of a fixed size and further derives its frame delay, preventing suboptimal performance of purely network-oriented designs. An analytic method for determining the target bit-rate replaces the trial-and-error updates of gradient-based methods, ensuring fast convergence to the available bandwidth. We evaluated the performance of BurstRTC and found that, compared with GCC, BurstRTC achieves up to $59.8 \%$ higher bit-rate and up to $\mathbf{4 8. 9 \%}$ lower frame delay. Further, compared with SQP and Pudica, BurstRTC can also reduce tail frame delay by up to $89.2 \%$, and improve average bit-rate by up to $15.6 \%$.