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Dependency-based fault diagnosis approach for SOA-based systems using Colored Petri Nets
- Source :
- Journal of King Saud University: Computer and Information Sciences, Vol 34, Iss 2, Pp 480-491 (2022)
- Publication Year :
- 2022
- Publisher :
- Elsevier, 2022.
-
Abstract
- A faulty situation occurred in Service Oriented Architecture (SOA) based systems can affect its functionality. It is challenging to guarantee the reliability of service utilization in a distributed, concurrent and dynamic composition of web services. This paper aims to present a fault detection approach of SOA using dependency analysis. Data and control dependencies are identified and a fault diagnosis approach based on these dependencies is proposed in this paper. The presented approach extends discrete state space techniques to simulate the concurrent and distributed behavior through Colored Petri Nets (CPNs) for the SOA-based systems in case of the faulty situation. Concrete translation from SOA based system to a CPN model is presented. Model-based technique is used and some heuristics are presented for dependency analysis and fault detection purpose. The experimental performance analysis shows the feasibility of our proposed approach.
- Subjects :
- Dependency (UML)
General Computer Science
computer.internet_protocol
Computer science
Distributed computing
Reliability (computer networking)
02 engineering and technology
computer.software_genre
Fault (power engineering)
Data dependency
Fault detection and isolation
020204 information systems
0202 electrical engineering, electronic engineering, information engineering
State space
SOA
Control dependency
Service Oriented Architecture
020207 software engineering
Service-oriented architecture
QA75.5-76.95
Fault
Electronic computers. Computer science
Web service
Heuristics
computer
Fault detection
Subjects
Details
- Language :
- English
- ISSN :
- 13191578
- Volume :
- 34
- Issue :
- 2
- Database :
- OpenAIRE
- Journal :
- Journal of King Saud University: Computer and Information Sciences
- Accession number :
- edsair.doi.dedup.....8b3d68da22c27c815d71f57ec33ff2ce