A Quality-driven Bit Rate Adaptation Method for Dynamic Adaptive Streaming over HTTP

In this paper, we study the problem of bit rate adaptation for dynamic adaptive streaming over HTTP (DASH). We first define a quality of experience (QoE) utility model by comprehensively considering video segment information, the segment encoding quality, hit rate switching and buffer playback interruption. Then, we propose a quality-driven bit rate adaptation method for HTTP adaptive streaming using the defined QoE utility model. By taking QoE, as the optimization object, we use Markov model and future segment size to predict future segment transmission process, and then make the optimal bit rate decision to achieve long-term user's experience quality. Simulation results show that the proposed quality-driven bit rate adaptation method can adaptively adjust the segment bit rate according to the network fluctuation, achieve good bandwidth adaptability and video smoothness, as well as improving the user's QoE.