离散概率标度生成的矩阵指数混合拟合

Q4 Computer Science Performance Evaluation Review Pub Date : 2023-09-28 DOI:10.1145/3626570.3626577
Julianna Bor, Giuliano Casale, William Knottenbelt, Evgenia Smirni, Andreas Stathopoulos
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引用次数: 0

摘要

矩阵指数(ME)分布推广了相型分布;然而,它们在排队理论中的应用由于难以检验其可行性而受到阻碍。我们提出了一种新的ME拟合算法,通过构造生成有效的分布。拟合过程中使用的ME分布是易于孤立控制的独立随机变量的乘积。因此,CDF和Mellin变换的计算简化了,使得可以使用这些措施进行拟合,而不受分布顺序的显著限制。跟踪驱动的排队模拟表明,所得到的分布产生了高度精确的结果。
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Fitting with matrix exponential mixtures generated by discrete probabilistic scaling
Matrix exponential (ME) distributions generalize phase-type distributions; however, their use in queueing theory is hampered by the difficulty of checking their feasibility. We propose a novel ME fitting algorithm that produces a valid distribution by construction. The ME distribution used during the fitting is a product of independent random variables that are easy to control in isolation. Consequently, the calculation of the CDF and the Mellin transform factorizes, making it possible to use these measures for the fitting without significant restriction on the distribution order. Trace-driven queueing simulations indicate that the resulting distributions yield highly accurate results.
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来源期刊
Performance Evaluation Review
Performance Evaluation Review Computer Science-Computer Networks and Communications
CiteScore
1.00
自引率
0.00%
发文量
193
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