矩阵模式兼容强随机界

A. Bušić, J. Fourneau
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引用次数: 11

摘要

随机边界是一种很有前途的QoS需求分析方法。事实上,证明实性能的一个界满足保证是足够的。然而,时间和空间的复杂性问题到目前为止还没有得到很好的理解。我们提出了一种新的算法来推导马尔可夫链的强随机界,该算法使用矩阵模式来指定边界矩阵应符合的结构性质。因此,我们可以得到一个更简单的马尔可夫链边界,其稳态解的数值计算更容易。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Matrix Pattern Compliant Strong Stochastic Bound
Stochastic bounds are a promising method to analyze QoS requirements. Indeed it is sufficient to prove that a bound of the real performance satisfies the guarantee. However, the time and space complexity issues are not well understood so far. We propose a new algorithm to derive a strong stochastic bound of a Markov chain, using a matrix pattern specifing the structural properties a bounding matrix should comply with. Thus we can obtain a simpler Markov chain bounding for which the numerical computation of the steady-state solution is easier.
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