Eric Fabre

Diagnosis of asynchronous discrete-event systems: a net unfolding approach

In this paper, we consider the diagnosis of asynchronous discrete event systems. We follow a so-called true concurrency approach, in which no global state and no global time is available. Instead, we use only local states in combination with a partial order model of time. Our basic mathematical tool is that of net unfoldings originating from the Petri net research area. This study was motivated by the problem of event correlation in telecommunications network management.

Fault Detection and Diagnosis in Distributed Systems: An Approach by Partially Stochastic Petri Nets

We address the problem of alarm correlation in large distributed systems. The key idea is to make use of the concurrence of events in order to separate and simplify the state estimation in a faulty system. Petri nets and their causality semantics are used to model concurrency. Special partially stochastic Petri nets are developed, that establish some kind of equivalence between concurrence and independence. The diagnosis problem is defined as the computation of the most likely history of the net given a sequence of observed alarms. Solutions are provided in four contexts, with a gradual complexity on the structure of observations.

Joint source-channel turbo decoding of entropy-coded sources

We analyze the dependencies between the variables involved in the source and channel coding chain. This analysis is carried out in the framework of Bayesian networks, which provide both an intuitive representation for the global model of the coding chain and a way of deriving joint (soft) decoding algorithms. Three sources of dependencies are involved in the chain: (1) the source model, a Markov chain of symbols; (2) the source coder model, based on a variable length code (VLC), for example a Huffman code; and (3) the channel coder, based on a convolutional error correcting code. Joint decoding relying on the hidden Markov model (HMM) of the global coding chain is intractable, except in trivial cases. We advocate instead an iterative procedure inspired from serial turbo codes, in which the three models of the coding chain are used alternately. This idea of using separately each factor of a big product model inside an iterative procedure usually requires the presence of an interleaver between successive components. We show that only one interleaver is necessary here, placed between the source coder and the channel coder. The decoding scheme we propose can be viewed as a turbo algorithm using alternately the intersymbol correlation due to the Markov source and the redundancy introduced by the channel code. The intermediary element, the source coder model, is used as a translator of soft information from the bit clock to the symbol clock.

Distributed Monitoring of Concurrent and Asynchronous Systems

In this paper we study the diagnosis of distributed asynchronous systems with concurrency. Diagnosis is performed by a peer-to-peer distributed architecture of supervisors. Our approach relies on Petri net unfoldings and event structures, as means to manipulate trajectories of systems with concurrency. This article is an extended version of the paper with same title, which appeared as a plenary address in the Proceedings of CONCUR’2003.

Markov nets: probabilistic models for distributed and concurrent systems

For distributed systems, i.e., large complex networked systems, there is a drastic difference between a local view and knowledge of the system, and its global view. Distributed systems have local state and time, but do not possess global state and time in the usual sense. In this paper, motivated by the monitoring of distributed systems and in particular of telecommunications networks, we develop a generalization of Markov chains and hidden Markov models for distributed and concurrent systems. By a concurrent system, we mean a system in which components may evolve independently, with sparse synchronizations. We follow a so-called true concurrency approach, in which neither global state nor global time are available. Instead, we use only local states in combination with a partial order model of time. Our basic mathematical tool is that of Petri net unfoldings.

Diagnosis of asynchronous discrete event systems, a net unfolding approach

This paper studies the diagnosis of asynchronous discrete event systems. We follow a so-called true concurrency approach, in which neither the global state nor global time are available. Instead, we use only local states in combination with a partial order model of time; our basic mathematical tool is that of Petri net unfoldings. This study was motivated by the problem of event correlation in telecommunications network management.

Distributed diagnosis for large discrete event dynamic systems

Abstract This paper presents a framework to deal with large systems, which cannot be handled as a whole. We propose to model them as a graph of interacting subsystems, and to base all processings on this factorization of the large system.

Distributed state reconstruction for discrete event systems

We consider the state estimation problem for stochastic discrete event dynamic system (DEDS) obtained by the parallel composition of several subsystems. A distributed inference algorithm is developed in the case of distributed observations. It is composed of asynchronous agents that only have a local view of the model and of observations. This algorithm only handles local states of subsystems, which is a way of avoiding the state explosion difficulty of large concurrent systems.

A Petri net approach to fault detection and diagnosis in distributed systems. I. Application to telecommunication networks, motivations, and modelling

This paper presents a new use of safe Petri nets in the field of distributed discrete event systems, with application to telecommunication network management. This study has in its long range objectives to provide a generic supervisor, which can be easily distributed on a set of sensors. Petri nets are used to provide both a model and an algorithm in fault management domain. Key features of our approach are (1) we take advantage of the ability of Petri Nets to model concurrency in distributed systems, (2) we refuse using the marking graph in our algorithms in order to avoid state explosion and thus rely instead in the so-called partial order semantics of Petri nets, and (3) our algorithms use net unfolding techniques and extend them to the probabilistic case by providing a generalized Viterbi algorithm. This paper concentrates on application, motivations, and modelling.

Partial order diagnosability of discrete event systems using petri net unfoldings

In truly asynchronous, distributed systems, neither global state nor global time are available. The diagnosis approach with Petri net unfoldings, motivated by the problem of event correlation in telecommunications network management and proposed, uses only local states in combination with a partial order model of time. Here, we give a definition of weak and strong diagnosability in terms of partially ordered executions, and characterize diagnosable systems; the characterizing property can be effectively verified using a finite complete prefix of the net unfolding.