Early Detection of QoE Deterioration in HTTP Adaptive Streaming

Abstract

Apart from video rate (or requested bitrate), Mean Opinion Score (MOS) has increasingly become a primary term representing Quality of Experience (QoE) in HTTP adaptive streaming (HAS). By monitoring this metric, QoE management can effectively maximize QoE for the users. However, due to various behaviors of particular commercial HAS players, deciding an appropriate monitoring interval has not been fully investigated yet. In this paper, an optimal interval is proposed to be equal to duration of a video chunk in order to aid service managers in early detecting QoE deterioration and limiting the probability of video rate deterioration. The optimal monitoring interval is evaluated by comparing with other values of interval in terms of ratio of video rate deterioration. Furthermore, MOS-based QoE monitoring method which takes into account the proposed interval is thus compared with video rate based monitoring method. The results show that with optimal interval, MOS monitoring guarantees a low ratio of video rate deterioration (around 10% for buffering state and 40% for steady state) and small average CPU Load (about 11.45%).

QABR: A QoE-Based Approach to Adaptive Bitrate Selection in Video Streaming Services

“…The QoE level reflects the user's perception to the service quality in accordance with his/her expectations during a streaming session. In fact, instantaneous QoE can reveal recent network condition since it reacts sensitively to negative events (e.g., rebuffering, bitrate switch) [5]. This shows the potential of applying QoE to adjusting streaming video bitrate.…”