Probabilistic modeling for IPTV network diagnosis and troubleshooting

In this paper, we propose two probabilistic modeling methods for IPTV network diagnosis, namely intolerable quality detection and device alarm analysis. The proposed methods can provide auxiliary information during troubleshooting processes, as well as inferring problematic devices automatically. Experimental results show that our models can distinguish problematic devices from normal ones and are more accurate than previous work under two evaluation criteria. Furthermore, we also demonstrate how we utilize these models in our actual network management system. It reveals that our methodologies are useful in finding out the service degradation proactively.