Assessing effect sizes of influence factors towards a QoE model for HTTP adaptive streaming

TLDR: In this work, the influence of several adaptation parameters, namely, switch amplitude, switching frequency, and recency effects, on Quality of Experience (QoE) is investigated and a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.

Abstract: HTTP Adaptive Streaming (HAS) is employed by more and more video streaming services in the Internet. It allows to adapt the downloaded video quality to the current network conditions, and thus, avoids stalling (i.e., playback interruptions) to the greatest possible extend. The adaptation of video streams is done by switching between different quality representation levels, which influences the user perceived quality of the video stream. In this work, the influence of several adaptation parameters, namely, switch amplitude (i.e., quality level difference), switching frequency, and recency effects, on Quality of Experience (QoE) is investigated. Therefore, crowdsourcing experiments were conducted in order to collect subjective ratings for different adaptation-related test conditions. The results of these subjective studies indicate the influence of the adaptation parameters, and based on these findings a simplified QoE model for HAS is presented, which only relies on the switch amplitude and the playback time of each layer.