Video Quality Monitoring based on Precomputed Frame Distortions

In the past decade, video streaming has taken over a large part of the current Internet traffic and more and more TV broadcasters and network providers extend their portfolio of video streaming services. With the growing expectations of video consumers with respect to the service quality, monitoring is an important aspect for network providers to detect possible performance problems or high network load. In parallel, emerging technologies like software defined networking or network virtualization introduce support for specialized networks which allow enhanced functionality in the network. This development enables more sophisticated monitoring techniques in the specialized networks which use knowledge about the video content to better predict the service quality at consumers. In this work, we present a SSIM-based monitoring technique and compare it with the current state-of-the-art which infers the service quality from the monitored packet loss. We further show how network conditions like packet loss or bursts influence the two different monitoring techniques.