Authors:
Gianfranco Lamperti
and
Marina Zanella
Affiliation:
Università degli Studi di Brescia, Italy
Keyword(s):
Diagnosis, supervision, discrete-event systems, temporal observations, indexing techniques, uncertainty.
Related
Ontology
Subjects/Areas/Topics:
Applications of Expert Systems
;
Artificial Intelligence and Decision Support Systems
;
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Society, e-Business and e-Government
;
Verification and Validation of Knowledge-Based Systems
;
Web Information Systems and Technologies
Abstract:
Observations play a major role in supervision and diagnosis of discrete-event systems (DESs). In a distributed, large-scale setting, the observation of a DES over a time interval is not perceived as a totally-ordered sequence of observable labels but, rather, as a directed acyclic graph, under uncertainty conditions. Problem solving, however, requires generating a surrogate of such a graph, the index space. Furthermore, the observation hypothesized so far has to be integrated at the reception of a new fragment of observation. This translates to the need for computing a new index space every time. Since such a computation is expensive, a naive generation of the index space from scratch at the occurrence of each observation fragment becomes prohibitive in real applications. To cope with this problem, the paper introduces an incremental technique for efficiently modeling and indexing temporal observations of DESs.