Name	Diagnosis of large scale discrete event systems
Begin	0
State	ongoing
Description	The problem is to monitor complex and large discrete-event systems (DES) such as telecommunication networks or web services. Two approaches are used in our research group. The first one consists in representing the system model as a discrete-event system by an automata. The diagnostic task consists in determining the trajectories (a sequence of states and events) compatible with the sequence of observations. From these trajectories, it is then easy to determine (identify and localize) the possible faults. In the second approach, the model consists in a set of predefined characteristic patterns. We use temporal patterns, called chronicles, represented by a set of temporally constrained events. The diagnostic task consists in recognizing these patterns by analyzing the flow of observed events.
Actions	Diagnosability and self-healability of discrete-event systems Distributed and incremental diagnosis of discrete-event systems Distributed monitoring with chronicles Optimal activity planning and scheduling for complex systems Self-adaptive monitoring systems