A state-space reduction method for computing the cell loss probability in ATM networks

Jun Yei, T. Yang
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引用次数: 3

Abstract

Cell loss performance analysis in ATM networks has been considered as one of the most important issues in congestion control which is vital to the success of the ATM technique. In recent years, numerous approaches have been proposed for the computation of the cell loss probability in ATM networks. Among them are the stochastic fluid-flow (SFF) method and the Markov modulated deterministic process (MMDP) approach. The MMDP approach is basically a discrete version of the SFF method and it is numerical stable. Both approaches, however, require a considerable amount of computation time for problems of practical size. In this paper, we propose a state-space reduction method for both approaches. The idea is to find an appropriate tradeoff between the efficiency and accuracy. As a result, the proposed approach performs very well in terms of both accuracy and efficiency. For cases of practical interest (in which cell loss probabilities ranges from 10/sup -6/ to 10/sup -10/) its computation time is only a fraction of one CPU second.<>
一种计算ATM网络中小区丢失概率的状态空间约简方法
ATM网络中的小区丢失性能分析是拥塞控制中的一个重要问题,它关系到ATM技术的成败。近年来,人们提出了许多计算ATM网络中小区丢失概率的方法。其中包括随机流体流动(SFF)方法和马尔可夫调制确定性过程(MMDP)方法。MMDP方法基本上是SFF方法的离散版本,它是数值稳定的。然而,对于实际规模的问题,这两种方法都需要相当多的计算时间。在本文中,我们针对这两种方法提出了一种状态空间约简方法。我们的想法是在效率和准确性之间找到一个适当的权衡。结果表明,该方法在精度和效率方面都有很好的表现。对于实际情况(其中单元丢失概率范围从10/sup -6/到10/sup -10/),其计算时间仅为一个CPU秒的一小部分。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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