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An Algorithmic Framework for Discrete-Time Flow-Level Simulation of Data Networks

机译:数据网络离散流级仿真的算法框架

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摘要

In this paper, we present a comprehensive algorithmic framework for discrete-time flow-level simulation of data networks. We first provide a simple algorithm based upon iterative equations useful for the simulation of networks with static traffic demands, and we show how to determine packet loss and throughput rates using a simple example network. We then extend these basic equations to a simulation method capable of handling queue and link delays in dynamic traffic scenarios and compare results from flow-level simulation to those obtained by packet-level simulation. Finally, we illustrate the tradeoff between computational complexity and simulation accuracy which is controlled by the duration of a single iteration interval Δ.
机译:在本文中,我们为数据网络的离散时间流级仿真提供了一个全面的算法框架。我们首先基于迭代方程式提供一种简单的算法,可用于模拟具有静态流量需求的网络,并展示如何使用一个简单的示例网络来确定数据包丢失和吞吐率。然后,我们将这些基本方程式扩展为一种能够处理动态流量场景中的队列和链接延迟的仿真方法,并将流级仿真的结果与数据包级仿真获得的结果进行比较。最后,我们说明了计算复杂度和仿真精度之间的折衷,该折衷由单个迭代间隔Δ的持续时间控制。

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