Enhancing QoE for Mobile Users by Environment-Aware HTTP Adaptive Streaming

HTTP adaptive streaming (HAS) has become a dominated media streaming paradigm in today's Internet, which enriches the user's experience by matching the video quality with the dynamic network conditions. A range of HAS mechanisms have been proposed to enhance the Quality of Experience (QoE). However, existing mechanisms ignore the environmental impact in the QoE evaluation of mobile users, while the popularity of mobile video allows users to watch videos in diversified scenarios. In this paper, we propose an environment-aware HAS scheme that fully concentrates on the different criteria for evaluating video QoE under different environments. Using the advantage of the sensors in mobile phones, the scheme constructs and validates a video QoE model based on environment perception and then designs a model-driven, environment-aware HAS rate adaptation algorithm. We also evaluate the scheme with an environment-aware DASH (Dynamic Adaptive Streaming over HTTP) player in real mobile environments. Compared to the benchmark HAS mechanism, the experimental results demonstrate that our scheme can provide appropriate differentiated rate adaptation for different environments, resulting in a higher QoE.