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Scalable k-out-of-n models for dependability analysis with Bayesian networks

Otto Bibartiu, Dürr, Frank, Kurt Rothermel, Ottenwälder, Beate and Andreas Grau

Reliability Engineering and System Safety, 2021, vol. 210, issue C

Abstract: Availability analysis is indispensable in evaluating the dependability of safety and business-critical systems, for which fault tree analysis (FTA) has proven very useful throughout research and industry. Fault trees (FT) can be analyzed by means of a rich set of mathematical models. One particular model are Bayesian networks (BNs) which have gained considerable popularity recently due to their powerful inference abilities. However, large-scale systems, as found in modern data centers for cloud computing, pose modeling challenges that require scalable availability models. An equivalent BN of a FT has no scalable representation for the k-out-of-n (k/n) voting gate because the conditional probability table that constitutes the k/n voting gate grows exponentially in n. Thus, the memory becomes the limiting factor.

Keywords: Availability; Scalability; Voting Gate; Fault-Tree; Bayesian networks (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (6)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:210:y:2021:i:c:s0951832021000910

DOI: 10.1016/j.ress.2021.107533

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