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Don't Just Go with the Flow: Cautionary Tales of Fluid Flow Approximation

机译:不要只是顺便:警示流体流动近似的故事

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Fluid flow approximation allows efficient analysis of large scale PEPA models. Given a model, this method outputs how the mean, variance, and any other moment of the model's stochastic behaviour evolves as a function of time. We investigate whether the method's results, i.e. moments of the behaviour, are sufficient to capture system's actual dynamics. We ran a series of experiments on a client-server model. For some parametrizations of the model, the model's behaviour can accurately be characterized by the fluid flow approximations of its moments. However, the experiments show that for some other parametrizations, these moments are not sufficient to capture the model's behaviour, highlighting a pitfall of relying only on the results of fluid flow analysis. The results suggest that the sufficiency of the fluid flow method for the analysis of a model depends on the model's concrete parametrization. They also make it clear that the existing criteria for deciding on the sufficiency of the fluid flow method are not robust.
机译:流体流近似允许有效分析大型百分比模型。鉴于模型,此方法输出模型的平均值,方差和模型的随机行为的任何其他时刻如何发展为时间的函数。我们调查了方法的结果,即行为的时刻,足以捕获系统的实际动态。我们在客户端 - 服务器模型上运行了一系列实验。对于模型的一些参数化,模型的行为可以精确地表征其时刻的流体流动近似。然而,实验表明,对于一些其他其他参数化,这些时刻不足以捕获模型的行为,突出仅依赖于流体流动分析结果的缺陷。结果表明,用于分析模型的流体流动方法的充分取决于模型的混凝土参数化。他们还明确表示,用于决定流体流动方法充足的现有标准并不稳健。

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