Gaetano Carlucci

Experimental investigation of the google congestion control for real-time flows

Enabling real-time communication over the Internet is of ever increasing importance due to the use of Internet for audio/video communication. The RTCWeb IETF working group has been established with the goal of standardizing a set of protocols for inter-operable real-time communication among Web browsers. In this paper we experimentally evaluate the Google Congestion Control (GCC) which has been recently proposed in the RTCWeb IETF WG. By setting up a controlled testbed, we have evaluated to what extent GCC flows are able to track the available bandwidth, while minimizing queuing delays, and fairly share the bottleneck with other GCC or TCP flows. We have found that the algorithm works as expected when a GCC flow accesses the bottleneck in isolation, whereas it is not able to provide a fair bandwidth utilization when a GCC flow shares the bottleneck with either a GCC or a TCP flow.

Understanding the Dynamic Behaviour of the Google Congestion Control for RTCWeb

Real-time communication over the Internet is of ever increasing importance due the diffusion of portable devices, such as smart phones or tablets, with enough processing capacity to support video conferencing applications. The RTCWeb working group has been established with the goal of standardizing a set of protocols for inter-operable real-time communication among Web browsers. In this paper we focus on the Google Congestion Control (GCC), recently proposed in such WG, which is based on a loss-based algorithm run at the sender and a delay-based algorithm executed at the receiver. In a recent work we have shown that a TCP flow can starve a GCC flow. In this work we show that this issue is due to a threshold mechanism employed by the delay-based controller. By carrying out an extensive experimental evaluation in a controlled testbed, we have found that, when the threshold is small, the delay-based algorithm prevails over the loss-based algorithm, which contains queuing delays and losses. However, a small threshold may lead to starvation of the GCC flow when sharing the bottleneck with a loss-based TCP flow.

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.

Modelling and control for web real-time communication

Congestion control for real-time media communication over the Internet is currently being addressed in IETF and W3C bodies aiming at standardizing a set of inter-operable protocols and APIs to enable real-time communication between Web browsers. In this paper we propose a mathematical model of the congestion control algorithm for real-time flows proposed by Google. Based on this model, we design a control algorithm that provides fair coexistence of real-time flows with TCP flows.

Controlling queuing delays for real-time communication: the interplay of E2E and AQM algorithms

Real-time media communication requires not only congestion control, but also minimization of queuing delays to provide interactivity. In this work we consider the case of real-time communication between web browsers (WebRTC) and we focus on the interplay of an end-to-end delay-based congestion control algorithm, i.e. the Google congestion control (GCC), with two delay-based AQM algorithms, namely CoDel and PIE, and two flow queuing schedulers, i.e. SFQ and Fq_Codel. Experimental investigations show that, when only GCC flows are considered, the end-to-end algorithm is able to contain queuing delays without AQMs. Moreover the interplay of GCC flows with PIE or CoDel leads to higher packet losses with respect to the case of a DropTail queue. In the presence of concurrent TCP traffic, PIE and CoDel reduce the queuing delays with respect to DropTail at the cost of increased packet losses. In this scenario flow queuing schedulers offer a better solution.

Congestion Control for WebRTC: Standardization Status and Open Issues

The WebRTC initiative has achieved impressive results in terms of the gained industrial interest, the penetration of the technology in end-user devices, and the ever growing community of developers. WebRTC is today supported by major mobile platforms and Internet browsers, allowing potentially billions of users to seamlessly establish real-time communication sessions. Among all the functionalities that must be implemented by WebRTC devices, congestion control is particularly important to ensure that the network operates properly while providing a satisfactory user experience. A working group that is focusing on this issue is the IETF RTP Media Congestion Avoidance Techniques (RMCAT), which aims at defining the requirements and designing congestion control algorithms to be used for the transport of real-time media flows over RTP. This article overviews the status of the standardization efforts that are taking place in the RMCAT working group. We discuss the choices involved in the design of media congestion control, the proposed algorithms, and the issues that are considered still open.

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.

Congestion control for real-time communications: A comparison between NADA and GCC

Congestion control for Web real-time communication (WebRTC) is a hot topic currently addressed at the IETF. Differently from congestion control for TCP, congestion control for WebRTC not only aims at containing packet losses, but also aims at minimizing queuing delays to provide interactivity. In this paper we describe two algorithms under discussion at IETF: Network Assisted Dynamic Adaptation (NADA) proposed by Cisco Systems and Google Congestion Control (GCC) proposed by Google. A performance comparison in a simulation environment is carried out. Results show that GCC exhibits slow convergence whereas NADA exhibits a remarkable oscillating behavior.