The Impact of Adaptation Strategies on Perceived Quality of HTTP Adaptive Streaming

Abstract

Changing network conditions like bandwidth fluctuations and resulting bad user experience issues (e.g. video freezes) pose severe challenges to Internet video streaming. To address this problem, an increasing number of video services utilizes HTTP adaptive streaming (HAS). HAS enables service providers to improve Quality of Experience (QoE) and resource utilization by incorporating information from different layers. However, these adaptation possibilities of HAS also introduce new perceivable impairments such as the fluctuation of audiovisual quality levels over time, which in turn lead to novel QoE-related research questions. The main contribution of this paper is the formulation of open research questions as well as a thorough systematic user-centric analysis of different quality adaptation dimensions and strategies. The underlying data has been acquired through two crowdsourcing and one lab study. The results provide guidance w.r.t. which encoding dimensions are combined best for the creation of the adaptation set and what type of adaptation strategy should be used. Furthermore it provides insights on the impact of adaptation frequency and the true QoE gain of adaptation over stallings.