Design and Analysis of QoE-Aware Quality Adaptation for DASH

The dynamics of the application-layer-based control loop of dynamic adaptive streaming over HTTP (DASH) make video bitrate selection for DASH a difficult problem. In this work, we provide a DASH quality adaptation algorithm, named SQUAD, that is specifically tailored to provide a high quality of experience (QoE). We review and provide new insights into the challenges for DASH rate estimation. We found that in addition to the ON-OFF behavior of DASH clients, there exists a discrepancy in the timescales that form the basis of the rate estimates across (i) different video segments and (ii) the rate control loops of DASH and Transmission Control Protocol (TCP). With these observations in mind, we design SQUAD aiming to maximize the average quality bitrate while minimizing the quality variations. We test our implementation of SQUAD together with a number of different quality adaptation algorithms under various conditions in the Global Environment for Networking Innovation testbed, as well as, in a series of measurements over the public Internet. Through a measurement study, we show that by sacrificing little to nothing in average quality bitrate, SQUAD can provide significantlygt ; better QoE in terms of quality switching and magnitude. In addition, we show that retransmission of higher-quality segments that were originally received in low-quality is feasible and improves the QoE.