Equivalent queueing networks and their use in approximate equilibrium analysis

Anurag Kumar
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引用次数: 8

Abstract

Most Markovian queueing networks that arise as models of stochastic congestion systems (e.g., communication networks and multiprogrammed computer systems) do not have a product form in their stationary probability distributions, and hence are not amenable to the simplicity of product-form analysis. In this paper we suggest an approach for systematically examining the validity of a class of approximation schemes that is based on the idea of equivalent networks and is used for the approximate equilibrium analysis of nonproduct-form networks. We study equivalent networks, and prove a generalization of the so-called “Norton's” Theorem for closed product-form networks in order to study and generalize the equivalent flow method for the approximate analysis of nonproduct-form queueing networks. We then present the results of a study of the approximation scheme as applied to a type of network model (called a central-server model) that arises frequently in modeling multiprogrammed computer systems. In this model the central server uses a priority discipline, so the resulting network is nonproduct form. This study demonstrates the situations under which the approximation can be expected to do well or poorly and the kinds of errors it introduces.
等效排队网络及其在近似均衡分析中的应用
大多数作为随机拥塞系统(例如,通信网络和多程序计算机系统)模型出现的马尔可夫排队网络在其平稳概率分布中没有乘积形式,因此不适合乘积形式分析的简单性。在本文中,我们提出了一种方法来系统地检查一类近似方案的有效性,该方案是基于等效网络的思想,并用于非积型网络的近似平衡分析。为了研究和推广非积型排队网络近似分析的等效流方法,我们研究了等效网络,并证明了封闭积型网络的“诺顿”定理的推广。然后,我们提出了将近似方案应用于多程序计算机系统建模中经常出现的一种网络模型(称为中央服务器模型)的研究结果。在这个模型中,中央服务器使用一个优先级规则,因此得到的网络是非产品形式的。本研究展示了在哪些情况下可以期望近似做得好或不好,以及它引入的各种误差。
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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