Comparing Fault Trees and Bayesian Networks for Dependability Analysis

Bobbio, Andrea; Portinale, Luigi; Minichino, Michele; Ciancamerla, Ester

doi:10.1007/3-540-48249-0_27

Cited by 26 publications

(26 citation statements)

References 4 publications

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“…A BN has a high efficiency and accuracy in uncertain inference, especially for complicated systems with highly-correlated elements (Qian et al, 2005;Doguc and Ramirez-Marquez, 2009;Bobbio et al, 1999;Xiao et al, 2008). In recent years, BNs have been widely used in areas with high degrees of uncertainty or mutual influences (Qian et al, 2005;Doguc and Ramirez-Marquez, 2009;Bobbio et al, 1999;Xiao et al, 2008).…”

Section: Bayesian Network (Bn)mentioning

confidence: 97%

“…Nevertheless, it is generally complicated to establish mutual relationships among nodes in the network solely based on the knowledge of engineers and experts. Therefore, several transformation processes from FTs to BNs have been proposed (Bobbio et al, 1999(Bobbio et al, , 2001Xiao et al, 2008;Boudali and Dugan, 2005;Marsh and Bearfield, 2007;Qian et al, 2005;Franke et al, 2009). In some past transformation, the conversion of logic gates in a FT into a BN is one-to-one; i.e., logic gates in a FT are converted into corresponding physical nodes in a BN.…”

Section: Bayesian Network (Bn)mentioning

confidence: 99%

“…At present, some scholars have proposed several systematic approaches to BN construction by FT transformation. The main techniques make use of and logic transforms into BNs to perform probabilistic analysis of event occurrences (Bobbio et al, 1999(Bobbio et al, , 2001Xiao et al, 2008;Boudali and Dugan, 2005;Marsh and Bearfield, 2007;Qian et al, 2005;Franke et al, 2009 studies regarded both events and logic gates in FTs as nodes in the BN. Nevertheless, these two have different definitions and purposes.…”

Section: Literature Surveymentioning

confidence: 99%

“…It's first to identify a particular undesired event as a top event, and then proceed from the event to its causes until the primary events are reached. The relationships between events and causes are commonly defined and represented by means of or logic gates (Bobbio et al, 1999(Bobbio et al, , 2001Xiao et al, 2008;Boudali and Dugan, 2005;Marsh and Bearfield, 2007;Qian et al, 2005;Franke et al, 2009).…”

Section: Conversion From a Ft To A Bnmentioning

confidence: 99%

See 3 more Smart Citations

Fall risk assessment of cantilever bridge projects using Bayesian network

Chen

Leu

2014

Safety Science

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Section: Bayesian Network (Bn)mentioning

confidence: 97%

Section: Bayesian Network (Bn)mentioning

confidence: 99%

Section: Literature Surveymentioning

confidence: 99%

Section: Conversion From a Ft To A Bnmentioning

confidence: 99%

See 2 more Smart Citations

Fall risk assessment of cantilever bridge projects using Bayesian network

Chen

Leu

2014

Safety Science

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“…Therefore, additional sources have to be used to provide knowledge on observations and their relations to component and functional failures. The similarity of FT and Bayesian Networks was first pointed out in [10] The authors have shown that fault trees can be converted to Bayesian Networks, which then can be used to implement system reliability analysis. They also prove that reliability analysis performed on BN is in some aspects better than combinatorial analysis performed on FT.…”

Section: Diagnostic Assistants Based On Bayesian Networkmentioning

confidence: 99%

An Efficient Framework for the Conversion of Fault Trees to Diagnostic Bayesian Network Models

Przytula

Milford

2006 IEEE Aerospace Conference

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Complex aerospace systems 1,2 cannot afford downtime to diagnose problems -the interruption of mission critical functions and prohibitive cost of lost business are unacceptable. Such systems are characterized by having many components and require a team of experts to diagnose problems after they occur or to assemble a knowledge database suitable for rapid model based diagnostics. In this paper we present an efficient and largely automated method for developing diagnostic Bayesian Network models. The models are created by exploiting existing domain knowledge in the form of reliability fault trees and diagnostic observation lists. The algorithms for conversion of the trees and databases into Bayesian Network models have been embedded in a C++ software tool and tested on examples of fault trees ranging from 10 to 800 nodes, which were developed for satellite systems.

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Availability analysis of redundant and replicated cloud services with Bayesian networks

Bibartiu

Dürr

Rothermel

et al. 2023

Quality & Reliability Eng

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Due to the growing complexity of modern data centers, failures are not uncommon any more. Therefore, fault tolerance mechanisms play a vital role in fulfilling the availability requirements. Multiple availability models have been proposed to assess compute systems, among which Bayesian network models have gained popularity in industry and research due to its powerful modeling formalism. In particular, this work focuses on assessing the availability of redundant and replicated cloud computing services with Bayesian networks. So far, research on availability has only focused on modeling either infrastructure or communication failures in Bayesian networks, but have not considered both simultaneously. This work addresses practical modeling challenges of assessing the availability of large-scale redundant and replicated services with Bayesian networks, including cascading and common-cause failures from the surrounding infrastructure and communication network. In order to ease the modeling task, this paper introduces a high-level modeling formalism to build such a Bayesian network automatically. Performance evaluations demonstrate the feasibility of the presented Bayesian network approach to assess the availability of largescale redundant and replicated services. This model is not only applicable in the domain of cloud computing it can also be applied for general cases of local and geo-distributed systems.

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Comparing Fault Trees and Bayesian Networks for Dependability Analysis

Cited by 26 publications

References 4 publications

Fall risk assessment of cantilever bridge projects using Bayesian network

Fall risk assessment of cantilever bridge projects using Bayesian network

An Efficient Framework for the Conversion of Fault Trees to Diagnostic Bayesian Network Models

Availability analysis of redundant and replicated cloud services with Bayesian networks

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