Modeling and Analysis of Dependable Systems
A Probabilistic Graphical Model Perspective
Nonfiction, Science & Nature, Mathematics, Probability, Computers, Advanced Computing, Artificial Intelligence, Statistics
| Author: | Luigi Portinale, Daniele Codetta Raiteri | ISBN: | 9789814612050 |
| Publisher: | World Scientific Publishing Company | Publication: | June 9, 2015 |
| Imprint: | WSPC | Language: | English |
| Author: | Luigi Portinale, Daniele Codetta Raiteri |
| ISBN: | 9789814612050 |
| Publisher: | World Scientific Publishing Company |
| Publication: | June 9, 2015 |
| Imprint: | WSPC |
| Language: | English |
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Contents:
- Dependability and Reliability
- Probabilistic Graphical Models
- From Fault Trees to Bayesian Networks
- From Dynamic Fault Tree to Dynamic Bayesian Networks
- Decision Theoretic Dependability
- The RADyBaN Tool: Supporting Dependability
- Case Study 1: Cascading Failures
- Case Study 2: Autonomous Fault Detection, Identification and Recovery
- Case Study 3: Security Assessment in Critical Infrastructures
- Case Study 4: Dynamic Reliability
The monographic volume addresses, in a systematic and comprehensive way, the state-of-the-art dependability (reliability, availability, risk and safety, security) of systems, using the Artificial Intelligence framework of Probabilistic Graphical Models (PGM). After a survey about the main concepts and methodologies adopted in dependability analysis, the book discusses the main features of PGM formalisms (like Bayesian and Decision Networks) and the advantages, both in terms of modeling and analysis, with respect to classical formalisms and model languages.
Methodologies for deriving PGMs from standard dependability formalisms will be introduced, by pointing out tools able to support such a process. Several case studies will be presented and analyzed to support the suitability of the use of PGMs in the study of dependable systems.
Contents:
- Dependability and Reliability
- Probabilistic Graphical Models
- From Fault Trees to Bayesian Networks
- From Dynamic Fault Tree to Dynamic Bayesian Networks
- Decision Theoretic Dependability
- The RADyBaN Tool: Supporting Dependability
- Case Study 1: Cascading Failures
- Case Study 2: Autonomous Fault Detection, Identification and Recovery
- Case Study 3: Security Assessment in Critical Infrastructures
- Case Study 4: Dynamic Reliability
