Scalable Differential Analysis of Process Algebra Models
Scalable Differential Analysis of Process Algebra Models
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DOI：
10.1109/tse.2010.82
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发表时间：
2012
影响因子：
7.4
通讯作者：
M. Tribastone;S. Gilmore;J. Hillston
中科院分区：
文献类型：
--
作者：
M. Tribastone;S. Gilmore;J. Hillston
由于状态空间爆炸这一众所周知的问题，用离散状态方法对大型软件系统进行精确的性能分析是困难的。本文考虑了随机过程代数PEPA的这一问题，给出了基于常微分方程组的马尔可夫链模型的确定性近似。通过一个分布式多线程应用程序的大量案例研究，评估了该近似的精度。
The exact performance analysis of large-scale software systems with discrete-state approaches is difficult because of the well-known problem of state-space explosion. This paper considers this problem with regard to the stochastic process algebra PEPA, presenting a deterministic approximation to the underlying Markov chain model based on ordinary differential equations. The accuracy of the approximation is assessed by means of a substantial case study of a distributed multithreaded application.