Analytical QoE models for bit-rate switching in dynamic adaptive streaming systems

Video streaming service in wireless networks is increasingly using dynamic selection of video bit-rates to provide a high quality of user experience (QoE). The bit-rate switching mechanism, performed at client side, plays a key role in determining QoE metrics. In this paper, we present the first analytical framework to compute starvation probability of playout buffer, continuous playback time and mean video quality, given the bit-rate switching logics. Wireless channel is modeled as a continuous time Markov process, and playout buffer is modeled as a fluid queue with Markov modulated fluid arrival. We construct a set of ordinary differential equations (ODEs) to characterize the dynamics of starvation probability and expected continuous playback time with regard to buffer length, and simple models to analyze mean bit-rate for different bit-rate switching algorithms. Our framework is very general in that by adding appropriate parameters, it can be utilized to predict the QoE metrics of dynamic adaptive streaming with a variety of features: i) buffer-aware bit-rate switching ii) (im)patience of the user, and iii) receiver-side flow control.