Measuring and modeling the impact of buffering and interrupts on streaming video quality of experience

Abstract

Streaming video clients use playout buffers to smooth out variations in network bitrates, especially important for mobile devices. The playout buffer sizes trade-off: the time delay before a video starts playing with interrupts when a video stops playing in the middle. The best buffer size a client should choose for the video and network conditions depends upon the relative impacts of buffering delays and interrupts on the user quality of experience (QoE). We design user study experiments that isolate buffering delays and interrupts, allowing for direct, quantitative comparisons of the impact on QoE for buffering delays versus interrupts. In our user study, over thirty users watched and rated 17 videos with a broad range of content, encoded with varying amounts of buffering delays and interrupts. Analysis of the data reveals interrupts more costly to QoE than the corresponding amount of buffering by a factor of about 2 to 1. The data is used to construct an analytic model of QoE which incorporates the impacts of buffering delays and interrupts, a model that can be a tool for assessing and improving how streaming video clients pick buffer sizes to maximize user QoE.