Modeling Gamer Quality-of-Experience Using a Real Cloud VR Gaming Testbed
Kuan-Yu Lee, Jia-Wei Fang, Yuan-Chun Sun, Cheng-Hsin Hsu
Abstract
Cloud Virtual Reality (VR) gaming offloads computationally-intensive VR games to resourceful data centers. Ensuring good Quality of Experience (QoE) in cloud VR gaming, however, is inherently challenging as VR gamers demand high visual quality, short response time, and low cybersickness. In this paper, we investigate the QoE of cloud VR gaming in multiple steps. First, we build a cloud VR gaming testbed, which allows us to measure various Quality of Service (QoS) metrics. Second, we carry out a user study to understand the effects of diverse factors, including encoding settings, network conditions, and game genres on gamer QoE, quantified by Mean Opinion Score (MOS). Using our user study results, we construct QoE models for cloud VR gaming, which to the best of our knowledge, has not been done in the literature. Last, we apply our QoE models to develop a bitrate allocation algorithm for multiple cloud VR gamers to achieve better overall QoE compared to the bandwidth-fair bitrate allocation.