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Exploiting the predictability of TCP's steady-state behavior to speed up network simulation

机译:利用TCP稳态行为的可预测性来加速网络仿真

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In discrete-event network simulation, a significant portion of resources and computation are dedicated to the creation and processing of packet transmission events. For large-scale network simulations with a large number of high-speed data flows, the processing of packet events is the most time consuming aspect of the simulation. We develop a technique that saves on the processing of packet events for TCP flows using the well established results showing that the average behavior of a TCP flow is predictable given a steady-state path condition. We exploit this to predict the average behavior of a TCP flow over a future period of time where steady-state conditions hold, thus allowing for a reduction (or elimination) of the processing required for packet events during this period. We consider two approaches to predicting TCP's steady-state behavior: using throughput formulas or by direct monitoring of a flow's throughput in a simulation. We design a simulation framework that provides the flexibility to incorporate this method of simulating TCP packet flows. Our goal is (1) to accommodate different network configurations, on/off flow behavior and interaction between predicted flows and packet-based flows; and (2) to preserve the statistical behavior of every entity in the system, from hosts to routers to links, so as to maintain the accuracy of the network simulation as a whole. In order to illustrate the promise of this idea we implement it in the context of the ns2 simulation system. A set of experiments illustrate the speedup and approximation of the simulation framework under different scenarios and for different network performance metrics.
机译:在离散事件网络仿真中,很大一部分资源和计算专用于数据包传输事件的创建和处理。对于具有大量高速数据流的大规模网络模拟,分组事件的处理是模拟中最耗时的方面。我们开发了一种技术,该技术使用良好建立的结果来节省TCP数据包事件的处理,该结果表明,在稳态路径条件下,TCP数据流的平均行为是可预测的。我们利用它来预测稳态条件保持的未来一段时间内TCP流的平均行为,从而减少(或消除)此期间数据包事件所需的处理。我们考虑了两种预测TCP稳态行为的方法:使用吞吐量公式或通过在仿真中直接监视流的吞吐量。我们设计了一个仿真框架,该框架提供了灵活的方法来合并这种模拟TCP数据包流的方法。我们的目标是(1)适应不同的网络配置,开/关流行为以及预测流和基于数据包的流之间的交互; (2)保留系统中每个主机(从主机到路由器再到链路)的统计行为,以保持整个网络仿真的准确性。为了说明该想法的希望,我们在ns2仿真系统的环境中实现了该想法。一组实验说明了在不同情况下和针对不同网络性能指标的仿真框架的加速和逼近。

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