https://www.mdu.se/

mdu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Evaluating the Hazardous Failure Rate of majority voting computer architectures by means of Bayesian Network models
Ansaldo STS, Italy ; Università di Napoli Federico II, Italy.ORCID iD: 0000-0002-2833-7196
Ansaldo STS, Italy ; Seconda Università di Napoli, Italy.
Università di Napoli Federico II, Italy.
Università di Napoli Federico II, Italy.
2007 (English)In: Proceedings of the European Safety and Reliability Conference 2007, ESREL 2007 - Risk, Reliability and Societal Safety, 2007, p. 1715-1721Conference paper, Published paper (Refereed)
Abstract [en]

Safety-critical control systems are usually based on majority voters. In order to assess the compliance of these architectures with international safety standards, the probability of the occurrence of unsafe events should be evaluated by developing and analyzing proper formal models. In this paper we demonstrate that a Bayesian Network (BN) model can be used to evaluate the Mean Time Between Hazardous Events (MTBHE) of voting architectures. The proposed modeling approach is applied to a "2 out of 2" ("2002") voter consisting of independent computing units. The results obtained from the analysis of the BN model of the "2002" voter can be easily extended to evaluate the hazardous failure rate of more complex voting architectures (e.g. Triple Modular Redundant architectures, based on a 2003 voting). Within this context, BNs have several advantages over other traditional approaches (e.g. Petri Nets or Markov Chains): the model can be directly derived from the analysis of the flow-chart describing the dynamic of hazardous failures and its evaluation is much more efficient, as BN solving algorithms are non state-based; moreover, sensitivity analyses can be automatically performed by using the available user friendly BN tools . Finally, the proposed BN model is quite general and can be easily adapted and/or extended to suit specific computing architectures and fault models. © 2007 Taylor & Francis Group.

Place, publisher, year, edition, pages
2007. p. 1715-1721
Keywords [en]
Architecture, Bayesian networks, Computer architecture, Computer networks, Computer science, Computer systems, Control systems, Distributed parameter networks, Failure analysis, Graph theory, Inference engines, Intelligent networks, Marine biology, Markov processes, Modal analysis, Petri nets, Regulatory compliance, Reliability, Sensitivity analysis, Speech analysis, Standardization, Bayesian Network models, Computing architectures, Computing units, Critical control systems, Failure rates, Fault models, Formal models, Hazardous events, International safety standards, Its evaluations, Majority voters, Majority voting, Markov chains, Modeling approaches, Triple modular redundant, User friendly, Quality assurance
National Category
Embedded Systems
Identifiers
URN: urn:nbn:se:mdh:diva-47805Scopus ID: 2-s2.0-56149090597ISBN: 0415447860 (print)ISBN: 9780415447867 (print)OAI: oai:DiVA.org:mdh-47805DiVA, id: diva2:1427357
Conference
European Safety and Reliability Conference 2007, ESREL 2007 - Risk, Reliability and Societal Safety, 25-27 June 2007, Stavanger
Available from: 2018-06-05 Created: 2020-04-29Bibliographically approved

Open Access in DiVA

No full text in DiVA

Scopus

Authority records

Flammini, Francesco

Search in DiVA

By author/editor
Flammini, Francesco
Embedded Systems

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 28 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf