Abstract
In this paper, we propose a novel Markov decision-based rate adaption scheme for DASH aiming to maximize the quality of user experience. To this end, our proposed method takes into account those key factors that have critical impact on visual quality, including video playback quality, video rate switching frequency and amplitude, buffer overflow/underflow, and buffer occupancy. And a dynamic reward function is carefully designed under three scenarios of buffer occupancy to measure the effectiveness of each transfer decision. Besides, to reduce computational complexity, we propose a low-complexity greedy algorithm to make it suitable for real-time video streaming. Our experiments in the real-world Internet demonstrate the good performance of the proposed method in terms of both objective and subjective visual quality.