Variation in QoE of Passive Gaming Video Streaming for Different Packet Loss Ratios

The rise in popularity of the streaming platforms for gaming videos like Twitch.tv results in more users watching and streaming gaming videos passively. These streaming videos show great dependence on Quality of Service (QoS) parameters like latency and packet loss. This motivates us to evaluate the Quality of Experience (QoE) of three popular streaming game videos for different Packet Loss Ratios (PLR). In this paper, using streaming gaming videos, we demonstrated the limitations of using Mean Opinion Score (MOS) to evaluate QoE. Using a novel method of data representation, we presented our results as distributions of user-rating at different PLR configuration and compared them with other subjective QoE evaluation methods like MOS and standard deviation of Opinion score (SOS). Our results show that evaluating QoE using MOS loses information about user diversity. Our findings also include SOS retaining user diversity but posing challenges to quantifying the QoE at varying PLR values. For streaming video games we show that QoE distributions evaluate user perception accurately. Our work in this paper also studies how different games with different content complexity, genre and pace are affected by PLR. Our results show that slow-paced games like FIFA 20 get affected more significantly by packet loss.