Modeling and simulating breakdown situations in telecommunication networks

Abstract

In this article we describe a framework for model-based diagnosis of telecommunication management networks. Our approach consists in modeling the system using temporal graphs and extended transducers and simulating given breakdown situations. The simulation process associates to each breakdown situation a set of sequences of observations, building up a learning database. This database is used to classify breakdown situations in the space of the observations. Our application uses imprecise temporal information expressed by pointisable intervals and requires their integration. In this article a new temporal transducer dealing with such information is proposed. Telecommunication management networks have a hierarchical structure; we propose a complete propagation algorithm of imprecise events in these systems.