Video Quality Monitoring in Future Networks
In the past decade, video streaming has taken over a large part of the current Internet traffic and is predominant on mobile devices. With the growing expectations of video consumers with respect to the service quality, monitoring is an important aspect for network providers to be able to rapidly react on performance problems or high network load and hence prevent service degradations. In parallel, emerging technologies like software defined networking or network virtualization introduce support for specialized networks which even allow enhanced functionality of nodes in the network. This development enables more sophisticated monitoring techniques in the network which use detailed knowledge about the video content to better predict the service quality at consumers.
Monitoring Based on Pre-Computed Frame Distortions
The first presented monitoring approach is a user-centric monitoring technique which uses precomputed knowledge about the video content in order to assess the service quality of video consumers. Therefore, we distribute video monitoring functionality to intermediate nodes in the network. The proposed monitoring technique takes into account the quality degradation due to lost frames and stores that information on the monitoring nodes in the network. The computation is based on the structural similarity (SSIM) metric and uses a mapping from SSIM to video quality in order to predict the quality at the video consumer.
Artikel in einem Journal, einer Zeitung oder einem Magazin
Dinh-Xuan, L., Popp, C., Burger, V., Wamser, F., Hoßfeld, T.: Impact of VNF Placements on QoE Monitoring in the Cloud. International Journal of Network Management. (2018).