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Reconfigurable GSPNs: A modeling formalism of evolvable discrete-event systems

机译:可重新配置的GSPN:可演化的离散事件系统的建模形式

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摘要

Nowadays, a wide range of systems are becoming structurally dynamic, variably interconnected, and highly complex. The use of classical formal approaches, such as Petri nets, in the design of such systems becomes neither convenient nor sufficient. Indeed, they cannot handle, in a natural way, the dynamic structure and the growing complexity of modern systems.Introducing reconfigurability in Petri nets, as well as generalized stochastic Petri nets increases the modeling power, but decreases the applicability of analysis techniques. In fact, several properties become undecidableIn this paper, we extend generalized stochastic Petri nets to a reconfigurable formalism, while maintaining verifiability with reduced complexity. The proposed approach identifies a set of properties that are preserved after reconfiguration. These properties are decidable with reduced time and space complexity. The use of the proposed formalism is illustrated through a running example. (C) 2019 Elsevier B.V. All rights reserved.
机译:如今,各种各样的系统都在结构上变得动态,相互连接且高度复杂。在此类系统的设计中使用经典的形式化方法(例如Petri网)既不方便也不充分。确实,它们无法自然地应对现代系统的动态结构和日益增长的复杂性。在Petri网以及广义随机Petri网中引入可重构性会增加建模能力,但会降低分析技术的适用性。实际上,有几个属性是不可确定的。在本文中,我们将广义随机Petri网扩展为可重构的形式主义,同时保持可验证性并降低了复杂性。所提出的方法确定了重新配置后保留的一组属性。通过减少时间和空间复杂性可以确定这些属性。通过运行示例说明了拟议形式主义的使用。 (C)2019 Elsevier B.V.保留所有权利。

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