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Computer Science > Multimedia

arXiv:2210.09651 (cs)
COVID-19 e-print

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[Submitted on 18 Oct 2022]

Title:Comparison of Popular Video Conferencing Apps Using Client-side Measurements on Different Backhaul Networks

Authors:Rohan Kumar, Dhruv Nagpal, Vinayak Naik, Dipanjan Chakraborty
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Abstract:Video conferencing platforms have been appropriated during the COVID-19 pandemic for different purposes, including classroom teaching. However, the platforms are not designed for many of these objectives. When users, like educationists, select a platform, it is unclear which platform will perform better given the same network and hardware resources to meet the required Quality of Experience (QoE). Similarly, when developers design a new video conferencing platform, they do not have clear guidelines for making design choices given the QoE requirements.
In this paper, we provide a set of networks and systems measurements, and quantitative user studies to measure the performance of video conferencing apps in terms of both, Quality of Service (QoS) and QoE. Using those metrics, we measure the performance of Google Meet, Microsoft Teams, and Zoom, which are three popular platforms in education and business. We find a substantial difference in how the three apps treat video and audio streams. We see that their choice of treatment affects their consumption of hardware resources. Our quantitative user studies confirm the findings of our quantitative measurements. While each platform has its benefits, we find that no app is ideal. A user can choose a suitable platform depending on which of the following, audio, video, or network bandwidth, CPU, or memory are more important.
Subjects: Multimedia (cs.MM); Networking and Internet Architecture (cs.NI)
ACM classes: H.5.1
Cite as: arXiv:2210.09651 [cs.MM]
  (or arXiv:2210.09651v1 [cs.MM] for this version)
  https://doi.org/10.48550/arXiv.2210.09651
Journal reference: Proceedings of the Twenty-Third International Symposium on Theory, Algorithmic Foundations, and Protocol Design for Mobile Networks and Mobile Computing 2022
Related DOI: https://doi.org/10.1145/3492866.3557734

Submission history

From: Vinayak Naik [view email]
[v1] Tue, 18 Oct 2022 07:38:08 UTC (7,297 KB)
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