Advanced MOS calculation for network based QoE Estimation of TCP streamed Video Services

Video streaming services, such as YouTube, are responsible for a major part of the transmitted data volume in the Internet and it is expected, that they will also strongly affect mobile networks. Streaming video quality mainly depends on the sustainable throughput achieved during transmission. In order to provide an acceptable video quality in mobile networks (with limited capacity resources), traffic engineering mechanisms have to be applied. For that, the streaming video quality needs to be measured and monitored permanently. In this paper we propose a network based Quality of Experience (QoE) estimation method for progressive download video, where the video file is downloaded into a buffer and played out from there. This allows for transparent monitoring without the requirement to install any monitoring tools on the users' end devices or on the server platform. Compared to already existing network based QoE estimation algorithms our method achieves a better monitoring performance with less processing effort and negligible loss in accuracy. The proposed Quality Monitoring (QMON) mechanism performs a playout buffer fill level estimation based on TCP flow observation in the measurement point and does a QoE evaluation based on the number and duration of occurred stalling events. The time elapsed from the last stall event to the current time is also taken into account for the calculation of the Mean Opinion Score (MOS). Besides the basic offline and online estimation method three differently powerful flavors of the estimation algorithm are presented in the paper. The QMON method has already been implemented and covers a wide range of video codecs like the highly compressing h.264 codec which is mainly used in the MP4 container as well as the new VP8 codec provided by Google in WebM container based download services. The former commonly used Flash Video service type is supported as well. The cutting edge scalable video codecs like Dynamic Adaptive Streaming over HTTP (DASH) also known as MPEG-DASH or Scalable Video Codec (SVC) are targeted too with the QMON method and are considered in this paper within a conceptual study.