Dynamic Adaptation Streaming over HTTP (DASH) enhances the Quality of Experience (QoE) for users by auto-matically switching quality levels according to network conditions. Various adaptation schemes have been proposed toselect the most suitable quality level during video playback. Adaptation schemes are currently based on the measured TCP throughput received by the video player. Althoughvideo buffer can mitigate throughput fluctuations, it does not take into account the effect of the transition of quality levels on the QoE.
In this paper, we propose a QoE-aware DASH system(or QDASH) to improve the user-perceived quality of videowatching. We integrate available bandwidth measurement into the video data probes with a measurement proxy archi-tecture. We have found that our available bandwidth measurement method facilitates the selection of video quality levels. Moreover, we assess the QoE of the quality transitions by carrying out subjective experiments. Our results show that users prefer a gradual quality change between the best and worst quality levels, instead of an abrupt switching. Hence, we propose a QoE-aware quality adaptation algorithm for DASH based on our findings. Finally, we integrate both network measurement and the QoE-aware quality adaptation into a comprehensive DASH system.
Via Nicolas Weil