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This paper presents insights on the promises of probabilistic modeling and machine learning for fault diagnosis in optical access networks. A Bayesian inference engine, called Probabilistic tool for GPON-FTTH Access Network self-DiAgnosis (PANDA), is applied to fault diagnosis of Gigabit capable Passive Optical Networks (GPON). PANDA approach has been assessed on real diagnosis data, showing very...
Network behavior modelling is a central issue for model-based approaches of self-diagnosis of telecommunication networks. There are two methods to build such models. The model can be built from expert knowledge acquired from network standards and/or the model can be learnt from data generated by network components by data mining algorithms. In a recent work, we proposed a model of architecture and...
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...
The dynamic and distributed nature of telecommunication networks makes complex the design of model-based approaches for network fault diagnosis. Most model-based approaches assume the prior existence of the model which is reduced to a static image of the network. Such models become rapidly obsolete when the network changes. We propose in this paper a 3-layered self-reconfigurable generic model of...
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