Towards QoE-Aware Dynamic Adaptive Streaming Over HTTP - Sobhani, Ashkan (Université d'Ottawa / University of Ottawa, 2017)
HTTP Adaptive Streaming (HAS) has now become ubiquitous, and it accounts for a large proportion of multimedia delivery over the Internet. Consequently, it poses new challenges for content providers and network operators. In this study, we aim to improve the user’s Quality of Experience (QoE) for HAS using from two main approaches including client centric approach and network assisted approach. In the client centric approach, we address the issue of enhancing the client’s QoE by proposing a fuzzy logic–based video bitrate adaptation and prediction mechanism for Dynamic Adaptive Streaming over HTTP (DASH) players. This adaptation mechanism allows HAS players to take appropriate actions sooner than existing methods to prevent playback interruptions caused by buffer underrun and reduce the ON-OFF traffic phenomena, which causes instability and unfairness among competing players. Our results show that compared to other studied methods, our proposed method has two advantages: better fairness among multiple competing players by almost 50% on average and as much as 80% as indicated by Jain’s fairness index, and better perceived quality of video by almost 8% on average and as much as 17%, according to the eMOS model. In the network assisted approach, we propose a novel mechanism for HAS stream adaptation in the context of wireless mobile networks. The proposed mechanism leverages recent advances in the 3GPP DASH specification, including the optional feature of QoE measurement and reporting for DASH clients. As part of the proposed mechanism, we formulate a utility-maximization problem that incorporates factors influencing QoE to specify the optimum value of Quality of Service (QoS)-related parameters for HAS streams within a wireless mobile network. The results of our simulations demonstrate that our proposed system results in better perceived quality of video, measured by Mean Opinion Score (MOS), by almost 7% on average, while lowering the freezing period by almost 20% on average across HAS users when compared to other approaches where HAS users only rely on local adaptation logics.
Keywords: Dynamic Adaptive Streaming Over HTTP; DASH; QoE; Optimization; Fairness; Fuzzy-Logic