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首页> 外文期刊>Reliability, IEEE Transactions on >Dynamic Hybrid Fault Modeling and Extended Evolutionary Game Theory for Reliability, Survivability and Fault Tolerance Analyses
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Dynamic Hybrid Fault Modeling and Extended Evolutionary Game Theory for Reliability, Survivability and Fault Tolerance Analyses

机译：动态混合故障建模和扩展进化博弈论，用于可靠性，生存性和容错分析

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摘要

We introduce a new layered modeling architecture consisting of dynamic hybrid fault modeling and extended evolutionary game theory for reliability, survivability, and fault tolerance analyses. The architecture extends traditional hybrid fault models and their relevant constraints in the Agreement algorithms with survival analysis, and evolutionary game theory. The dynamic hybrid fault modeling (i) transforms hybrid fault models into time- and covariate-dependent models; (ii) makes real-time prediction of reliability more realistic, and allows for real-time prediction of fault-tolerance; (iii) sets the foundation for integrating hybrid fault models with reliability and survivability analyses by integrating them with evolutionary game modeling; and (iv) extends evolutionary game theory by stochastically modeling the survival (or fitness) and behavior of ‘game players.’ To analyse survivability, we extend dynamic hybrid fault modeling with a third-layer, operational level modeling, to develop the three-layer survivability analysis approach (dynamic hybrid fault modeling constitutes the tactical and strategic levels). From the perspective of evolutionary game modeling, the two mathematical fields, i.e., survival analysis and agreement algorithms, which we applied for developing dynamic hybrid fault modeling, can also be utilized to extend the power of evolutionary game theory in modeling complex engineering, biological (ecological), and social systems. Indeed, a common property of the areas where our extensions to evolutionary game theory can be advantageous is that the risk analysis and management are a core issue. Survival analysis (including competing risks analysis, and multivariate survival analysis) offers powerful modeling tools to analyse time-, space-, and/or covariate-dependent uncertainty, vulnerability, and/or frailty which ‘game players’ may experience. The agreement algorithms, which are not limited to the agreement algorith-n-nms from distributed computing, when applied to extend evolutionary game modeling, can be any problem (game system) specific rules (algorithms or models) that can be utilized to dynamically check the consensus among game players. We expect that the modeling architecture and approaches discussed in the study should be implemented as a software environment to deal with the necessary sophistication. Evolutionary computing should be particularly convenient to serve as the core optimization engine, and should simplify the implementation. Accordingly, a brief discussion on the software architecture is presented.
机译：我们引入了一种新的分层建模架构，该架构包含动态混合故障建模和扩展的演化博弈论，以进行可靠性，生存能力和容错分析。该架构扩展了传统的混合故障模型及其在具有生存分析和进化博弈论的协议算法中的相关约束。动态混合故障建模（i）将混合故障模型转换为与时间和协变量相关的模型； （ii）使可靠性的实时预测更加切合实际，并允许对容错进行实时预测； （iii）通过将混合故障模型与演化博弈模型集成，为混合故障模型与可靠性和生存性分析的集成奠定基础； （iv）通过对“游戏玩家”的生存（或适应性）和行为进行随机建模来扩展进化博弈论。为分析生存力，我们将动态混合故障建模与第三层，运营水平建模相结合，以开发三层层生存能力分析方法（动态混合故障建模构成了战术和战略层面）。从进化博弈建模的角度来看，我们用于开发动态混合故障建模的两个数学领域，即生存分析和协议算法，也可以用来扩展进化博弈论在建模复杂工程，生物学（生态）和社会系统。确实，我们对演化博弈论进行扩展可能会有利的领域的共同属性是，风险分析和管理是一个核心问题。生存分析（包括竞争风险分析和多变量生存分析）提供了强大的建模工具，可以分析“游戏玩家”可能经历的时间，空间和/或协变量相关的不确定性，脆弱性和/或脆弱性。协议算法不限于来自分布式计算的协议算法-n-nm，当应用于扩展演化游戏建模时，可以是可用于动态检查的任何问题（游戏系统）特定规则（算法或模型）玩家之间的共识。我们希望研究中讨论的建模架构和方法应作为一种软件环境来实现，以处理必要的复杂性。演化计算应该特别方便地用作核心优化引擎，并且应该简化实现。因此，提出了关于软件体系结构的简短讨论。

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