Paper title: Direct propagation of network QoS distribution to subjective QoE for Video on Demand applications using VP9 codec.

The increasing popularity of the Video on Demand (VoD) applications like Netflix and YouTube has caused a large increase in video streaming over the network. To increase subscriptions and avoid customer churn, service providers are keen to evaluate the end-user experience more effectively. In this paper, we present an approach that can be used to evaluate the distribution of the Quality of Experience (QoE) metric evaluated from the measured Quality of Service (QoS) distributions. By using the network QoS measurements of delay and jitter, we find the probability density functions (PDF) for these parameters. Focussing on VoD applications employing improved VP9 codec (as used by Netflix) we use subjective testing and regression to map QoE onto jitter. The resulting QoE model and theory of direct propagation of probability density function was used to evaluate the distribution of QoE. We found that the empirical delay and jitter measurements follow a lognormal distribution whose characteristic parameters, sigma ( σ) and mu ( μ), vary for different network providers in the UK. Our results indicate that, even for slight variations of the underlying jitter distribution, the QoE distribution shows significant variations. These variations were recorded and presented as confidence intervals for four leading UK network providers