快速模型参数化工具及其应用

Kun-Chan Lan, J. Heidemann
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引用次数: 15

摘要

仿真和分析的有效性在很大程度上依赖于良好的网络流量模型。然而,由于网络的巨大异构性和快速变化,对互联网流量进行建模和仿真是非常困难的。互联网流量的统计特性不仅随着时间的推移而不断变化,而且在位置和方向等其他维度上也会发生变化。之前,我们已经开发了一个工具RAMP,它支持从实时网络测量中快速参数化流量模型。在本文中,我们首先扩展RAMP以支持近实时跟踪驱动的仿真。接下来,我们通过三个案例研究来演示RAMP的应用:生成用于仿真的真实流量模型,生成高带宽合成网络轨迹,以及恶意流量的分析和建模。最后,我们讨论了使用RAMP进行交通建模的一些经验教训。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A tool for RApid model parameterization and its applications
The utility of simulations and analysis heavily relies on good models of network traffic. However, it is difficult to model and simulate the Internet traffic because of the network's great heterogeneity and rapid change. The statistical properties of Internet traffic not only constantly change over time but also vary in other dimensions such as locations and directions. Previously we have developed a tool RAMP that supports rapid parameterization of traffic models from live network measurements. In this paper, we first extend RAMP to support near-real-time trace-driven simulation. Next, we demonstrate the applications of RAMP via three case studies: generation of realistic traffic model for simulation, generation of high bandwidth synthetic network traces, and analysis and modeling of malicious traffic. Finally, we discuss some lessons we learned from using RAMP for traffic modeling.
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