Video streaming on the Internet is increasingly using Dynamic Adaptive Streaming over HTTP (DASH), in which the video is converted into various quality levels and divided into two-second segments. A client can then adjust its video quality over time by choosing to download the appropriate quality level for a given segment using standard HTTP. Scalable Video Coding (SVC) is a promising enhancement to the DASH protocol. With SVC, segments are divided into subset bitstream blocks. At playback, blocks received for a given segment are combined to additively increase the current quality. Unlike traditional DASH, which downloads segments serially, this encoding creates a large space of possible ways to download a video; for example, if given a variable download rate, when should the client try to maximize the current segment's video quality, and when should it instead play it safe and ensure a minimum level of quality for future segments? In this work, we examine the impact of SVC on the client's quality selection policy, with the goal of maximizing a performance metric quantifying user satisfaction. We use acombination of analysis, dynamic programming, and simulation to show that, in many cases, a client should use a diagonal quality selection policy, balancing both of the aforementioned concerns, and that the slope of the best policy flattens out as the variation in download rateincreases.



College and Department

Physical and Mathematical Sciences; Computer Science



Date Submitted


Document Type





Video Streaming, SVC, DASH, Quality Selection Algorithms