Video Conferencing and Flow-Rate Fairness: A First Look at Zoom and the Impact of Flow-Queuing AQM

TL;DR

This paper examines how Zoom's video conferencing congestion control impacts flow-rate fairness, queuing delays, and user experience, especially under Active Queue Management (AQM), revealing challenges in fairness and quality of experience.

Contribution

It provides the first analysis of Zoom's congestion control behavior, its fairness issues, and the effects of AQM on video conferencing traffic and user experience.

Findings

Zoom uses 2-3 times more bandwidth than TCP in low-bandwidth scenarios.

AQM reduces queuing delays but causes high packet loss for Zoom.

User study suggests QoE is not improved by AQM for Zoom.

Abstract

Congestion control is essential for the stability of the Internet and the corresponding algorithms are commonly evaluated for interoperability based on flow-rate fairness. In contrast, video conferencing software such as Zoom uses custom congestion control algorithms whose fairness behavior is mostly unknown. Aggravatingly, video conferencing has recently seen a drastic increase in use - partly caused by the COVID-19 pandemic - and could hence negatively affect how available Internet resources are shared. In this paper, we thus investigate the flow-rate fairness of video conferencing congestion control at the example of Zoom and influences of deploying AQM. We find that Zoom is slow to react to bandwidth changes and uses two to three times the bandwidth of TCP in low-bandwidth scenarios. Moreover, also when competing with delay aware congestion control such as BBR, we see high queuing delays. AQM reduces these queuing delays and can equalize the bandwidth use when used with flow-queuing. However, it then introduces high packet loss for Zoom, leaving the question how delay and loss affect Zoom's QoE. We hence show a preliminary user study in the appendix which indicates that the QoE is at least not improved and should be studied further.