Z-Iteration: Efficient Estimation of Instantaneous Measuresin Time-Dependent Multi-Class Systems
Z-Iteration: Efficient Estimation of Instantaneous Measuresin Time-Dependent Multi-Class Systems
复制标题
Z 迭代：瞬态测量的高效估计瞬态多类系统
DOI：
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发表时间：
1998
期刊：
影响因子：
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通讯作者：
A. Shankar
中科院分区：
文献类型：
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作者：
I. Matta;A. Shankar
多类多资源（MCMR）系统，其中每一类客户需要一组特定的资源，是常见的。这些系统通常在稳态条件下进行分析。我们描述了一个简单的数值分析方法，称为Z-迭代，估计瞬时（和稳态）的概率措施的时间依赖系统。其核心思想是用稳态测量值之间的关系来近似某些瞬时测量值之间的关系，并利用这种近似来求解动态流方程。我们展示了Z-迭代的一般性，通过将其应用于集成通信网络，并行数据库服务器和分布式批处理系统。对精确的数值解和离散事件模拟的验证显示的Z-迭代的精度和计算优势。
Multiple-class multiple-resource (MCMR) systems, where each class of customers requires a particular set of resources, are common. These systems are often analyzed under steady-state conditions. We describe a simple numerical-analytical method, referred to as Z-iteration, to estimate instantaneous (and steady-state) probability measures of time-dependent systems. The key idea is to approximate the relationship between certain instantaneous measures by the relationship between their steady-state counterparts, and use this approximation to solve dynamic ow equations. We show the generality of the Z-iteration by applying it to an integrated communication network, a parallel database server, and a distributed batch system. Validations against exact numerical solutions and discrete-event simulations show the accuracy and computational advantages of the Z-iteration.