ENABLING OPTIMIZATIONS OF VIDEO DELIVERY IN HTTP ADAPTIVE STREAMING

Abstract

In shared network environments, providing a satisfactory viewer Quality-of-Experience (QoE) for multiple concurrent video players is an arduous task and becomes very critical. Despite a plethora of solutions towards better QoE, existing works have been designed for specific environments and have shown good performance under certain circumstances. Nonetheless, most of them have not succeeded in achieving an acceptable viewer QoE level required by today's applications. The key focus of this dissertation is to bridge the long-standing gap between the optimization of the viewers' QoE, video players' competition for the available bandwidth, and their growing bandwidth demand, with respect to group fairness and network conditions in the existing best-effort network infrastructure. To achieve this objective, this dissertation goes one step beyond existing client-driven solutions, by providing the design, implementation, and evaluation of a novel suite of Adaptive BitRate (ABR) related solutions where the goal is to avoid HAS scalability issues (quality instability, QoE unfairness, and network resource underutilization/oversubscription) while maximizing the viewers' QoE in a fair and efficient way.