Stefan Holmer

Analysis and design of the google congestion control for web real-time communication (WebRTC)

Video conferencing applications require low latency and high bandwidth. Standard TCP is not suitable for video conferencing since its reliability and in order delivery mechanisms induce large latency. Recently the idea of using the delay gradient to infer congestion is appearing again and is gaining momentum. In this paper we present an algorithm that is based on estimating through a Kalman filter the end-to-end one way delay variation which is experienced by packets traveling from a sender to a destination. This estimate is compared to an adaptive threshold to dynamically throttle the sending rate. The control algorithm has been implemented over the RTP/RTCP protocol and is currently used in Google Hangouts and in the Chrome WebRTC stack. Experiments have been carried out to evaluate the algorithm performance in the case of variable link capacity, presence of heterogeneous or homogeneous concurrent traffic, and backward path traffic.

Handling packet loss in WebRTC

WebRTC is an open-source real-time interactive audio and video communication framework. This paper discusses some of the mechanisms utilized in WebRTC to handle packet losses in the video communication path. Various system details are discussed and an adaptive hybrid NACK/FEC method with temporal layers is presented. Results are shown to quantify how the method controls the quality trade-offs for real-time video communication.

Congestion Control for Web Real-Time Communication

Applications requiring real-time communication (RTC) between Internet peers are ever increasing. RTC requires not only congestion control but also minimization of queuing delays to provide interactivity. It is known that the well-established transmission control protocol congestion control is not suitable for RTC due to its retransmissions and in-order delivery mechanisms, which induce significant latency. In this paper, we propose a novel congestion control algorithm for RTC, which is based on the main idea of estimating—using a Kalman Filter—the end-to-end one-way delay variation which is experienced by packets traveling from a sender to a destination. This estimate is compared with a dynamic threshold and drives the dynamics of a controller located at the receiver, which aims at maintaining queuing delays low, while a loss-based controller located at the sender acts when losses are detected. The proposed congestion control algorithm has been adopted by Google Chrome. Extensive experimental evaluations have shown that the algorithm contains queuing delays while providing intra and inter protocol fairness along with full link utilization.

Making Google Congestion Control robust over Wi-Fi networks using packet grouping

Google congestion control (GCC) has been proposed for the case of delay sensitive traffic (i.e. video-conference) in the WebRTC framework. In this paper we analyze the effect of wireless channel outages on the GCC. We have observed that, when a channel outage ends, there are packets that arrive at the receiver as a burst. This behavior impairs the delay-based controller employed by GCC, resulting in throughput degradation. We propose a solution to make GCC robust with respect to channel outages. In particular, by grouping packets that arrive in a burst, the delay-based controller avoids to misinterpret a burst as network congestion. In order to prove the effectiveness of the proposed solution we have carried out a trace-driven experimental evaluation in a loaded Wi-Fi scenario.