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arXiv 1207.0874cs.LO
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并发进程的弱马尔可夫互模拟同余和精确CTMC级集结

Weak Markovian Bisimulation Congruences and Exact CTMC-Level Aggregations for Concurrent Processes

Marco Bernardo

摘要:

我们最近定义了一个弱马尔可夫互模拟等价的集成时间设置,它减少了序列的指数定时的内部行动,个人指数定时的内部行动具有相同的平均持续时间和执行概率的相应序列。这种弱马尔可夫互模拟等价是一个同余序列过程的抽象和原来诱导一个确切的CTMC级聚集在稳态所有考虑的过程。然而,它并不是平行合成的一致性。在本文中,我们展示了如何推广的等价性的方式,一个合理的权衡抽象,组合性和精确性之间实现了并发进程。我们将看到,通过增强并行计算中的抽象能力,可以检索关于并行组合的同余属性,所得到的CTMC级聚合仅对于所考虑过程的某个子集在稳定状态下是精确的。

英文摘要:

We have recently defined a weak Markovian bisimulation equivalence in an integrated-time setting, which reduces sequences of exponentially timed internal actions to individual exponentially timed internal actions having the same average duration and execution probability as the corresponding sequences. This weak Markovian bisimulation equivalence is a congruence for sequential processes with abstraction and turns out to induce an exact CTMC-level aggregation at steady state for all the considered processes. However, it is not a congruence with respect to parallel composition. In this paper, we show how to generalize the equivalence in a way that a reasonable tradeoff among abstraction, compositionality, and exactness is achieved for concurrent processes. We will see that, by enhancing the abstraction capability in the presence of concurrent computations, it is possible to retrieve the congruence property with respect to parallel composition, with the resulting CTMC-level aggregation being exact at steady state only for a certain subset of the considered processes.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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