QOE CONTINUUM DRIVEN HTTP ADAPTIVE STREAMING OVER MULTI-CLIENT WIRELESS NETWORKS

Different from traditional HTTP adaptive streaming (HAS) in which only one client is considered, HAS over multi-client wireless networks faces new challenges. The Quality of Experience (QoE) of users becomes unstable due to users' competition for shared bandwidth. It is thus important to accurately estimate the perceived experience of users and then adapt the streaming process accordingly. Furthermore, the QoE fairness among multiple clients subscribing to the same services shall also be addressed. In this research, we propose a QoE continuum driven HAS adaptation algorithm to address these challenges. We model the QoE continuum as an integrated consideration of cumulative playback quality and playback smoothness. Based on this model, we jointly optimize the quality adaptation of multiple users by considering both QoE history and channel status. Moreover, we propose to use quantization parameter and segment size to represent the video files in a fine-grained fashion, in order to more effectively capture the bandwidth fluctuation. The results from extensive simulations show that the proposed scheme can provide balanced and satisfactory QoE among multiple clients.