Paper Info
Title
Model-Based Diagnosability Analysis for Web Services
Abstract
In this paper we deal with the problem of model-based diagnosability analysis for Web Services. The goal of diagnosability analysis is to determine whether the information one can observe during service execution is sufficient to precisely locate (by means of diagnostic reasoning) the source of the problem. The major difficulty in the context of Web Services is that models are distributed and no single entity has a global view of the complete model. In the paper we propose an approach that computes diagnosability for the decentralized diagnostic framework, described in [1], based on a Supervisor coordinating several Local Diagnosers. We also show that diagnosability analysis can be performed without requiring the Local Diagnosers different operations than those needed for diagnosis. The proposed approach is incremental: each fault is first analyzed independently of the occurrence of other faults, then the results are used to analyze combinations of behavioral modes, avoiding in most cases an exhaustive check of all combinations.
Year
DOI
Venue
2007
10.1007/978-3-540-74782-6_4
AI*IA
Keywords
Field
DocType
computes diagnosability,local diagnosers,model-based diagnosability analysis,web services,decentralized diagnostic framework,diagnostic reasoning,diagnosability analysis,complete model,behavioral mode,web service
Supervisor,Data mining,Discrete event system,Computer science,Web service,Diagnostic reasoning
Conference
Volume
ISSN
Citations 
4733
0302-9743
2
PageRank 
References 
Authors
0.49
12
5
Name
Order
Citations
PageRank
Stefano Bocconi115013.11
Claudia Picardi252637.98
Xavier Pucel331.60
Daniele Theseider Dupré4473131.30
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