Exploiting Petri nets to support fault tree based dependability analysis

A. Bobbio, G. Franceschinis, R. Gaeta, L. Portinale
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引用次数: 30

Abstract

This paper explores the possibility of converting Fault Trees (FT) into the Generalized Stochastic Petri Net (GSPN) formalism. Starting from a slightly modified version of a conversion algorithm already appeared in the literature, the aim of the paper is to exploit the modeling and decision power of GSPN for both the qualitative and the quantitative analysis of the modeled system. The qualitative analysis resorts to structural properties and is based on a T-invariant analysis. In order to alleviate the state space explosion problem deriving from the quantitative analysis, the paper proposes a new formalism for FT, that is referred to as High Level FT (HLFT), in which replicated redundant units are folded and indexed. Starting from the HLFT formalism, a new conversion algorithm is provided that translates a HLFT into a Stochastic Well-formed Net (SWN). The computational saving of using SWN with respect to GSPN is carefully examined considering an example of a fault-tolerant multiprocessor system.
利用Petri网支持基于故障树的可靠性分析
本文探讨了将故障树(FT)转化为广义随机Petri网(GSPN)形式的可能性。从文献中已经出现的转换算法的稍微修改版本开始,本文的目的是利用GSPN的建模和决策能力对建模系统进行定性和定量分析。定性分析采用结构性质,并基于t不变分析。为了缓解定量分析带来的状态空间爆炸问题,本文提出了一种新的傅里叶变换形式,即对复制冗余单元进行折叠和索引的高阶傅里叶变换(High Level FT, HLFT)。从HLFT的形式化出发,提出了一种将HLFT转化为随机良形网络的新算法。考虑到一个容错多处理器系统的例子,仔细检查了使用SWN相对于GSPN的计算节省。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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