A Cumulative Quality Model for HTTP Adaptive Streaming

Abstract

The quality of adaptive streaming may fluctuate strongly during a session. Therefore, a challenge is how to evaluate the quality of a session over time. In this study, a cumulative quality model is proposed for HTTP adaptive streaming. The model is based on the concept of a sliding window of video segments over a session. It is found that the minimum window quality, the last window quality, and the average window quality are key components of the cumulative quality model. In addition, the proposed model is applicable to real-time quality monitoring, which is especially important for cost-effective evaluation of streaming technologies and as basis for adaptive quality mechanisms.