弱马尔可夫双相似性:从优先/加权的内部即时动作中提取

M. Bernardo, A. Aldini
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引用次数: 12

摘要

马尔可夫过程演算为推理并发系统的功能和性能方面提供了一个有用的框架。这是通过考虑动作名称及其指数分布持续时间的行为等效来实现的。马尔可夫过程演算的可表达性的一个显著扩展来自于采用类似gspn的即时动作,即具有零持续时间并具有优先级和权重的动作。由于从功能和性能的角度来看,内部即时动作都是不可观察的,因此在本文中,我们解决了定义从此类动作抽象出来的马尔可夫双相似性的弱变体的问题。我们证明了所提出的等价是一个同余,并承认一类良好优先级的过程项的健全和完整的公理化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Weak Markovian Bisimilarity: Abstracting from Prioritized/Weighted Internal Immediate Actions
Markovian process calculi constitute a useful framework for reasoning about the functional and performance aspects of concurrent systems. This is achieved by means of behavioral equivalences that take into account both the action names and their exponentially distributed durations. A notable extension to the expressiveness of Markovian process calculi derives from the adoption of GSPNlike immediate actions, i.e. actions with a zero duration and equipped with a priority level and a weight. Since internal immediate actions are unobservable both from the functional viewpoint and from the performance viewpoint, in this paper we tackle the problem of defining a weak variant of Markovian bisimilarity that abstracts from such actions. We show that the proposed equivalence is a congruence and admits a sound and complete axiomatization for the class of well-prioritized process terms.
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