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arXiv 1709.07171cs.FL
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概率时间自动机最大期望终止时间的计算

Computing Maximal Expected Termination Time of Probabilistic Timed Automata

Omar Al-Bataineh, Michael Fisher, David Rosenblum

摘要:

研究了概率时间自动机(PTA)模型在系统最终将终止的条件下,最大期望终止时间的计算问题。该问题可能表现出高计算复杂性,特别是当分析中的自动机包含可能非常频繁地重复的循环(由于非常高的概率,例如p =0.999)时。这样的循环会降低典型模型检验算法的性能,因为重复循环的可能性任意缓慢地收敛到零。我们介绍了一种加速技术,可以应用于改善这些周期的执行,通过折叠他们的迭代。循环PTA的加速过程由处理连续执行循环所产生的累积定时和概率信息所需的几个正式步骤组成。加速的好处是双重的。首先,它有助于降低问题的计算复杂性,而不会对分析结果产生不利影响。第二,它可以把“最坏情况下的执行时间”的PTA问题的范围内的模型检验技术的可行性。据我们所知,这是第一个工作,解决了加速执行的周期,表现出时间和概率行为的问题。

英文摘要:

The paper addresses the problem of computing maximal expected time to termination of probabilistic timed automata (PTA) models, under the condition that the system will, eventually, terminate. This problem can exhibit high computational complexity, in particular when the automaton under analysis contains cycles that may be repeated very often (due to very high probabilities, e.g. p =0.999). Such cycles can degrade the performance of typical model checking algorithms, as the likelihood of repeating the cycle converges to zero arbitrarily slowly. We introduce an acceleration technique that can be applied to improve the execution of such cycles by collapsing their iterations. The acceleration process of a cyclic PTA consists of several formal steps necessary to handle the cumulative timing and probability information that result from successive executions of a cycle. The advantages of acceleration are twofold. First, it helps to reduce the computational complexity of the problem without adversely affecting the outcome of the analysis. Second, it can bring the "worst case execution time" problem of PTAs within the bounds of feasibility for model checking techniques. To our knowledge, this is the first work that addresses the problem of accelerating execution of cycles that exhibit both timing and probabilistic behavior.

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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