Terminal reliability using binary decision diagrams

Singh, Harpreet; Vaithilingam, S.; Anne, RadhaKiranMaye; Anneberg, L.

doi:10.1016/0026-2714(95)00087-9

Cited by 16 publications

(9 citation statements)

References 3 publications

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“…e.g. Prime Implication(PI) [6,7] Binary Decision Diagram (BBD) [8], Markov regenerative stochastic Petri nets [9], Shannon expansion using truncation [10], Object oriented approaches [11], Factoring theorem [12], or Pattern recognition [13].However, UDMC is a repairable system, those method is not appropriate.…”

Section: A Methodology For Quantitative Reliability Analysismentioning

confidence: 97%

Evaluation of reliability and safety for an underwater dry maintenance cabin

Liang

Hong

Zhang

et al. 2009

2009 8th International Conference on Reliability, Maintainability and Safety

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Effectiveness of an underwater dry maintenance cabin (UDMC) is mainly determined by its reliability, availability and safety. In this paper, the reliability and safety of a UDMS is evaluated qualitatively and quantitatively via fault tree analysis (FTA). According to the composition, mission characteristic and operational condition of the UDMC, three kinds of typical failure patterns are identified. All ultimate causes, or combination of causes that are responsible for or contribute to the top events, are recognized via FTA. Then, based on minimum cut sets, probability of system failure is calculated by numerical simulations which show that UDMC is of high reliability and safety. Moreover, with the aid of theory of the critical importance, the weak links of the system, which are required in making an effective preventative maintenance strategy, are identified. Finally, suggestions to improve the reliability and safety of the UDMC are proposed ① .

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Section: A Methodology For Quantitative Reliability Analysismentioning

confidence: 97%

Evaluation of reliability and safety for an underwater dry maintenance cabin

Liang

Hong

Zhang

et al. 2009

2009 8th International Conference on Reliability, Maintainability and Safety

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“…BDD or ordered BDD (OBDD) based methods [14,15,19,22,33,47] have been widely used in analyzing network reliability since 1990s. BDD is a directed graph based on Shannon decomposition.…”

Section: Bdd Methods For Reliability Evaluationmentioning

confidence: 99%

“…Kelly and Bartlett [4,5,18,19] compare the digraph methods with the fault-tree methods in system fault diagnostics. In the 1990s, binary decision diagrams (BDD) based approaches [11,14,15,19,22,33,47] became increasingly popular for network analysis. A strength of BDD-based methods is that the BDD provides a succinct and disjoint description of system success/failure.…”

Section: Introductionmentioning

confidence: 99%

Two-terminal reliability analysis for multi-phase communication networks

Lu¹,

Innal²,

Xiao-yue³

et al. 2016

EiN

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Two-Terminal reliabiliTy analysis for mulTi-phase communicaTion neTworks analiza niezawodności par Terminali w wielofazowych sieciach komunikacyjnych Większość badań niezawodności sieci ogólnie przyjąć, że struktury systemu nie zmieniają się w czasie. W artykule przedstawiono koncepcję systemów sieciowych wielofazowych (MPNS) rozpatrywanie dynamicznych właściwości sieci i analizy niezawodności MPNS. MPNS niezawodność jest oceniany przez cross-fazowego schematu decyzyjnego binarny (BDD

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“…In the field of reliability, BDDs were first used by Rauzy [14] and Coudert [15]. For the terminal-pair reliability problem, Singh et functions from the network structure and store them in a BDD [16]. Kuo, Lu and Yeh employed Ordered BDDs (OBDDs) and proposed an elegant way to avoid redundant computations by recognizing isomorphic subgraphs [10].…”

Section: Introductionmentioning

confidence: 99%

A Novel Variable Ordering Heuristic for BDD-based K-Terminal Reliability

Lê¹,

Weidendorfer²,

Walter

2014

2014 44th Annual IEEE/IFIP International Conference on Dependable Systems and Networks

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Modern exact methods solving the NP-hard kterminal reliability problem are based on Binary Decision Diagrams (BDDs). The system redundancy structure represented by the input graph is converted into a BDD whose size highly depends on the predetermined variable ordering. As finding the optimal available ordering has exponential complexity, a heuristic must be used. Currently, the breadth-first-search is considered to be state-of-the-art. Based on Hardy's decomposition approach, we derive a novel static heuristic which yields significantly smaller BDD sizes for a wide variety of network structures, especially irregular ones. As a result, runtime and memory requirements can be drastically reduced for BDD-based reliability methods. Applying the decomposition method with the new heuristic to three medium-sized irregular networks from the literature, an average speedup of around 9,400 is gained and the memory consumption drops to less than 0.1 percent.

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Terminal reliability using binary decision diagrams

Cited by 16 publications

References 3 publications

Evaluation of reliability and safety for an underwater dry maintenance cabin

Evaluation of reliability and safety for an underwater dry maintenance cabin

Two-terminal reliability analysis for multi-phase communication networks

A Novel Variable Ordering Heuristic for BDD-based K-Terminal Reliability

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