  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.
