A highly adaptable probabilistic model for self-diagnosis of GPON-FTTH access networks

Model-based approaches for self-diagnosis of telecommunication networks develop reasonings based on formal and explicit representation of network structure and network behavior. Network behavior modeling is a central issue for these methods. In a recent work, we have proposed a model of architecture and fault propagation of the FTTH (Fiber To The Home) access networks based on GPON (Gigabit capable Passive Optical Network). This model is based on a Bayesian network which encodes expert knowledge about the transport network and the connection network of subscribers. In this paper we extend this model by designing a model of the distribution network which fits to the various engineering techniques of the GPON-FTTH network. We carried out self-diagnosis of an operating GPON-FTTH network based on these two models. The performance of self-diagnostic of the new model is evaluated with respect to the previous model of the GPON-FTTH network.