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Infinite- and finite-buffer markov fluid queues: A unified analysis

机译:无限缓冲和有限缓冲的马尔可夫流体队列:统一分析

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摘要

In this paper, we study Markov fluid queues where the net fluid rate to a single-buffer system varies with respect to the state of an underlying continuous-time Markov chain. We present a novel algorithmic approach to solve numerically for the steady-state solution of such queues. Using this approach, both infinite- and finite-buffer cases are studied. We show that the solution of the infinite-buffer case is reduced to the solution of a generalized spectral divide-and-conquer (SDC) problem applied on a certain matrix pencil. Moreover, this SDC problem does not require the individual computation of any eigenvalues and eigenvectors. Via the solution for the SDC problem, a matrix-exponential representation for the steady-state queue-length distribution is obtained. The finite-buffer case, on the other hand, requires a similar but different decomposition, the so-called additive decomposition (AD). Using the AD, we obtain a modified matrix-exponential representation for the steady-state queue-length distribution. The proposed approach for the finite-buffer case is shown not to have the numerical stability problems reported in the literature.
机译:在本文中,我们研究了马尔可夫流体队列,其中单缓冲系统的净流体速率相对于基础连续时间马尔可夫链的状态而变化。我们提出了一种新颖的算法方法来数值求解此类队列的稳态解。使用这种方法,研究了无限缓冲和有限缓冲两种情况。我们证明了无限缓冲情况的解决方案被简化为应用于特定矩阵铅笔的广义频谱分而治之(SDC)问题的解决方案。此外,此SDC问题不需要任何特征值和特征向量的单独计算。通过解决SDC问题,获得了稳态队列长度分布的矩阵指数表示。另一方面,有限缓冲的情况需要类似但不同的分解,即所谓的加性分解(AD)。使用AD,我们获得了稳态队列长度分布的经修改的矩阵指数表示。所提出的有限缓冲情况下的方法没有文献报道的数值稳定性问题。

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