VR Traffic Dataset on Broad Range of End-User Activities

Abstract

With the emergence of new internet traffic types in modern transport networks, it has become critical for service providers to understand the structure of that traffic and predict peaks of that load for planning infrastructure expansion. Several studies have investigated 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 real residential user session recorded for at least half an hour. Newly collected data helped show that some gaming VR traffic activities have a high share of uplink traffic and require symmetric user links. Also, we have figured out that the gaming phase of the overall gameplay is more sensitive to the channel resources reduction than the higher bitrate game launch phase. Hence, we recommend it as a source of traffic distribution for channel sizing model creation. From the gaming phase, capture intervals of more than 100 s contain the most representative information for modeling activity.