A QOE-driven approach to rate adaptation for dynamic adaptive streaming over http

摘要

In this paper, we focus on the quality of experience (QoE) optimization for dynamic adaptive streaming over HTTP (DASH) services. First, we propose a QoE evaluation model based on playback continuity, segment media quality and perceptual quality fluctuations caused by bitrate switching. Plenty of subjective mean-opinion-score (MOS) tests have shown a good correlation between this model and subjective perception. Second, based on our QoE evaluation model, we formulate the rate adaptation for DASH as a constrained convex optimization problem. The design objective is to maximize the overall QoE for the end users while keep the receiver buffer from underflow. Numerous experiment results demonstrate that our proposed rate adaptation scheme achieves near optimal tradeoff between overall QoE and playback continuity.