VR traffic dataset on broad range of end-user activities

With the emergence of new Internet traffic types in modern transport networks, it becomes 1 critical for the service providers to understand the structure of that traffic and predict peaks of that load for planning infrastructure expansion. Several studies are investigating traffic parameters for Virtual Reality (VR) applications. Still, most of them test only a partial range of user activities during a limited time interval. This work creates a dataset of captures from a broader spectrum of VR activities performed with a Meta Quest 2 headset, with the duration of each user session recorded at least half an hour. Results of the measurements demonstrate the optimal trace length reflecting all traffic features and also show that VR traffic appears to be more symmetric than the traffic of other user network activities, which is a novel insight, not reflected as per our best knowledge in similar traffic studies.