Controlling Queuing Delays for Real-Time Communication: The Interplay of E2E and AQM Algorithms

Gaetano Carlucci, Luca De Cicco, Saverio Mascolo.
Abstract

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.

testbed

Public review by Fabian Bustamante

For an increasingly important class of Internet applications – such as videoconference and personalized live streaming – high delay, rather than limited bandwidth, is the main obstacle to improved performance. A common problem that impacts this class of applications is “bufferbloat”, where excess buffering in the network causes high latency and jitter. Solutions for persistently full buffer problems, active queue management (AQM) schemes such as the original RED, have been known for two decades. Yet, while RED is simple and effective at reducing persistent queues is not widely or consistently configured and enabled in routers and sometimes directly unavailable.

Recent focus on bufferbloat has brought a number of new AQM proposals, including PIE and CoDel, which explicitly control the queuing delay and have no knobs for operators, users or implementers to adjust. This paper considers the interplay between some of these AQM protocols and the new end-to-end delay-based congestion control algorithm, Google Congestion Control (GCC) part of the WebRTC framework.

Two sets of reviewers agree that, while the topic is well established, there is still significant work to be done and the authors contribute and incremental yet valuable analysis in the context of real-time communication and the increasingly popular WebRTC. The authors were encouraged to release the software used for conducting their measurements to let other researchers in the community replicate their results and explore some of the variants and alternative scenarios raised by different reviewers.

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