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(to be completed)

 


ThinkMind // International Journal On Advances in Telecommunications, volume 3, numbers 3 and 4, 2010 // View article tele_v3_n34_2010_17


A Semantic-oriented Framework for System Diagnosis

Authors:
Manuela Popescu
Pascal Lorenz
Jean Marc Nicod

Keywords: system diagnosis, diagnosis validation, knowledge transfer; ontology-based diagnosis; semantic tag clouds; progressive ontology; temporal features

Abstract:
In the field of system and network diagnosis, there is a variety of modeling and inference methods reported in literature. However, very few are focusing on the validation and knowledge transfer in case of similar symptoms. Many researchers targeted the use of a generic diagnosis framework, semantic-oriented solutions, and temporal aspects related to diagnosis validation. Event correlation and action triggering are essential for an accurate diagnosis decision. However, no industry-wide solution was considered so far. In this article, we are proposing an adaptive framework for diagnosis validation and transfer of information from successful outcomes for future use and optimization of the diagnostic activity. It is shown that this mechanism allows a post-validation of successful diagnosis actions, optimizing the diagnosis process and increasing its accuracy. We are presenting a series of ontology-driven mechanisms for system diagnosis. Mainly, we introduce event ontology and concepts related to semantic tag clouds and show how to manage the activities to build an ontology-based diagnosis. Additionally, we consider temporal aspects related to diagnosis validation. Event correlation and action triggering are essential for an accurate diagnosis decision. There are several time-related challenges referring to event timestamps, timely event correlations, and timely corrective actions, in both absolute time (precise moment), or relative time (between events, actions, and events and actions). We consider a series of temporal operators defining the event relative temporal position that allows a more fine grain interpretation of the system behavior. A combination of proposed mechanisms is used to complete the main functions of a diagnosis engine.

Pages: 173 to 193

Copyright: Copyright (c) to authors, 2010. Used with permission.

Publication date: April 6, 2011

Published in: journal

ISSN: 1942-2601

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