使用ipc推导PEPA模型中的通过时间密度:帝国PEPA编译器

J. Bradley, N. Dingle, S. Gilmore, W. Knottenbelt
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引用次数: 78

摘要

提出了一种从高级随机过程代数模型中定义和提取通行时间密度的方法。我们的高级形式是PEPA,一种流行的马尔可夫过程代数,用于表达组合性能模型。通过将PEPA模型和通道规范编译成DNAmaca形式,引入ipc工具对PEPA指定的通道时间密度和模型进行处理。DNAmaca是一种建立的建模语言,用于非常大的马尔可夫链和半马尔可夫链的低级规范。我们提供了ipc/DNAmaca的性能结果,并与另一个支持PEPA的工具PRISM进行了比较。最后,我们为高可用性Web服务器的案例研究生成传递时间密度和分位数。
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Derivation of passage-time densities in PEPA models using ipc: the imperial PEPA compiler
A technique for defining and extracting passage-time densities from high-level stochastic process algebra models is presented. Our high-level formalism is PEPA, a popular Markovian process algebra for expressing compositional performance models. We introduce ipc, a tool which can process PEPA-specified passage-time densities and models by compiling the PEPA model and passage specification into the DNAmaca formalism. DNAmaca is an established modelling language for the low-level specification of very large Markov and semiMarkov chains. We provide performance results for ipc/DNAmaca and comparisons with another tool which supports PEPA, PRISM. Finally, we generate passage-time densities and quantiles for a case study of a high-availability Web server.
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