Quality-Control algorithm for adaptive streaming services over wireless channels

Dynamic Adaptive Streaming over HTTP (DASH) is a recent MPEG standard for IP video delivery whose aim is the convergence of existing adaptive-streaming proprietary solutions. However, it does not impose any adaptation logic for selecting the quality of the media segments requested by the client, which is crucial to cope effectively with bandwidth fluctuations, notably in wireless channels. We therefore propose a solution to this control problem through Stochastic Dynamic Programming (SDP). This approach requires a probabilistic characterization of the system, as well as the definition of a cost function that the control strategy aims to minimize. This cost function is designed taking into account factors that may influence the quality perceived by the users. Unlike previous works, which compute control policies online by learning from experience, our algorithm solves the control problem offline, leading promptly to better results. In addition, we compared our algorithm to others during a streaming simulation and we analyzed the objective results by means of a Quality of Experience (QoE) oriented metric. Moreover, we conducted subjective tests to complete the evaluation of the performance of our algorithm. The results show that our proposal outperforms the other approaches in terms of both the QoE-oriented metric and the subjective evaluation.