Measuring the Performance and Network Utilization of Popular Video Conferencing Applications

TL;DR

This study analyzes the resource usage and performance of popular video conferencing apps like Zoom, Google Meet, and Microsoft Teams under various network conditions, revealing significant differences and challenges in bandwidth management.

Contribution

It provides a comprehensive empirical analysis of three major VCAs, highlighting their resource requirements, performance under constraints, and effects of usage modalities.

Findings

Average utilization ranges from 0.8 to 1.9 Mbps.

Some VCAs take up to 50 seconds to recover from capacity reductions.

Bandwidth fairness varies due to proprietary congestion control algorithms.

Abstract

Video conferencing applications (VCAs) have become a critical Internet application, even more so during the COVID-19 pandemic, as users worldwide now rely on them for work, school, and telehealth. It is thus increasingly important to understand the resource requirements of different VCAs and how they perform under different network conditions, including: how much speed (upstream and downstream throughput) a VCA needs to support high quality of experience; how VCAs perform under temporary reductions in available capacity; how they compete with themselves, with each other, and with other applications; and how usage modality (e.g., number of participants) affects utilization. We study three modern VCAs: Zoom, Google Meet, and Microsoft Teams. Answers to these questions differ substantially depending on VCA. First, the average utilization on an unconstrained link varies between 0.8 Mbps and 1.9 Mbps. Given temporary reduction of capacity, some VCAs can take as long as 50 seconds to recover to steady state. Differences in proprietary congestion control algorithms also result in unfair bandwidth allocations: in constrained bandwidth settings, one Zoom video conference can consume more than 75% of the available bandwidth when competing with another VCA (e.g., Meet, Teams). For some VCAs, client utilization can decrease as the number of participants increases, due to the reduced video resolution of each participant's video stream given a larger number of participants. Finally, one participant's viewing mode (e.g., pinning a speaker) can affect the upstream utilization of other participants.