Fusion, propagation, and structuring in belief networks
Artificial Intelligence
Petr nets, algebras, morphisms, and compositionality
Information and Computation
Distributed algorithms and protocols
Distributed algorithms and protocols
Logical Time in Distributed Computing Systems
Computer - Distributed computing systems: separate resources acting as one
Symbolic model checking: an approach to the state explosion problem
Symbolic model checking: an approach to the state explosion problem
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Handbook of graph grammars and computing by graph transformation: volume I. foundations
Diagnosis of large active systems
Artificial Intelligence
Diagnosis of discrete-event systems from uncertain temporal observations
Artificial Intelligence
Coordinated Decentralized Protocols for Failure Diagnosisof Discrete Event Systems
Discrete Event Dynamic Systems
A General Architecture for Decentralized Supervisory Control of Discrete-Event Systems
Discrete Event Dynamic Systems
Categories of Models for Concurrency
Seminar on Concurrency, Carnegie-Mellon University
Using Unfoldings to Avoid the State Explosion Problem in the Verification of Asynchronous Circuits
CAV '92 Proceedings of the Fourth International Workshop on Computer Aided Verification
On the Effect of Communication Delays in Failure Diagnosis of Decentralized Discrete Event Systems
Discrete Event Dynamic Systems
WODES '02 Proceedings of the Sixth International Workshop on Discrete Event Systems (WODES'02)
Distributed Diagnosis for Qualitative Systems
WODES '02 Proceedings of the Sixth International Workshop on Discrete Event Systems (WODES'02)
Undecidable problems of decentralized observation and control on regular languages
Information Processing Letters
Distributed Monitoring of Concurrent and Asynchronous Systems*
Discrete Event Dynamic Systems
Hierarchical Fault Diagnosis for Discrete-Event Systems under Global Consistency
Discrete Event Dynamic Systems
Information and Computation
Flexible diagnosis of discrete-event systems by similarity-based reasoning techniques
Artificial Intelligence
Distributed diagnosis of discrete-event systems using Petri nets
ICATPN'03 Proceedings of the 24th international conference on Applications and theory of Petri nets
Distributed unfolding of petri nets
FOSSACS'06 Proceedings of the 9th European joint conference on Foundations of Software Science and Computation Structures
Time supervision of concurrent systems using symbolic unfoldings of time petri nets
FORMATS'05 Proceedings of the Third international conference on Formal Modeling and Analysis of Timed Systems
Branching cells as local states for event structures and nets: probabilistic applications
FOSSACS'05 Proceedings of the 8th international conference on Foundations of Software Science and Computation Structures
Decentralized failure diagnosis of discrete event systems
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Fault detection and isolation based on fuzzy automata
Information Sciences: an International Journal
What topology tells us about diagnosability in partial order semantics
Discrete Event Dynamic Systems
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Monitoring or diagnosis of large scale distributed Discrete Event Systems with asynchronous communication is a demanding task. Ensuring that the methods developed for Discrete Event Systems properly scale up to such systems is a challenge. In this paper we explain why the use of partial orders cannot be avoided in order to achieve this objective. To support this claim, we try to push classical techniques (parallel composition of automata and languages) to their limits and we eventually discover that partial order models arise at some point. We focus on on-line techniques, where a key difficulty is the choice of proper data structures to represent the set of all runs of a distributed system, in a modular way. We discuss the use of previously known structures such as execution trees and unfoldings. We propose a novel and more compact data structure called "trellis." Then, we show how all the above data structures can be used in performing distributed monitoring and diagnosis. The techniques reported here were used in an industrial context for fault management and alarm correlation in telecommunications networks. This paper is an extended and improved version of the plenary address that was given by the second author at WODES' 2006.