Chronicle modeling by Petri nets for distributed detection of process failures

In this paper, distributed detection of process failures is studied. Erroneous evolutions, corresponding to failure situations, are described by chronicles. Every chronicle is composed of a set of events, and of a set of time constraints between these events. A chronicle can be decomposed into sub-chronicles distributed into several monitoring sites (systems). The objective of a monitoring site is to recognize a sub-chronicle. A specific reasoning considering relative time between event occurrences is proposed to provide time consistency of the mechanisms set Combining t-time Petri nets and p-time Petri nets, p-t-time Petri nets are used to represent these chronicles. When the Petri net reaches a particular state, a sub-chronicle is recognized. A symptom is detected when all the sub-chronicles associated to the initial chronicle have been recognized.