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A Min-Max Problem for the Computation of the Cycle Time Lower Bound in Interval-Based Time Petri Nets

机译:基于间隔的时间Petri网中循环时间下界的最小-最大问题

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摘要

The time Petri net with firing frequency intervals (TPNF) is a modeling formalism used to specify system behavior under timing and frequency constraints. Efficient techniques exist to evaluate the performance of TPNF models based on the computation of bounds of performance metrics (e.g., transition throughput, place marking). In this paper, we propose a min-max problem to compute the cycle time of a transition under optimistic assumptions. That is, we are interested in computing the lower bound. We will demonstrate that such a problem is related to a maximization linear programming problem (LP-max) previously stated in the literature, to compute the throughput upper bound of the transition. The main advantage of the min-max problem compared to the LP-max is that, in addition to the optimal value, the optimal solutions provide useful feedback to the analyst on the system behavior (e.g., performance bottlenecks). We have implemented two solution algorithms, using CPLEX APIs, to solve the min-max problem, and have compared their performance using a benchmark of TPNF models, several of these being case studies. Finally, we have applied the min-max technique for the vulnerability analysis of a critical infrastructure, i.e., the Saudi Arabian crude-oil distribution network.
机译:具有触发频率间隔的时间Petri网(TPNF)是一种建模形式,用于指定在时序和频率约束下的系统行为。存在基于性能指标的边界的计算(例如,过渡吞吐量,位置标记)来评估TPNF模型的性能的有效技术。在本文中,我们提出了一个最小-最大问题来计算乐观假设下的过渡周期。也就是说,我们对计算下限感兴趣。我们将证明该问题与先前在文献中所述的最大化线性规划问题(LP-max)有关,以计算过渡的吞吐量上限。与LP-max相比,min-max问题的主要优势在于,除了最佳值之外,最佳解决方案还可以为分析师提供有关系统行为(例如性能瓶颈)的有用反馈。我们使用CPLEX API实现了两种解决方案算法,以解决最小-最大问题,并使用TPNF模型的基准比较了它们的性能,其中一些是案例研究。最后,我们将min-max技术应用于关键基础设施(即沙特阿拉伯原油分销网络)的脆弱性分析。

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