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Integrated fluid and packet network simulations

机译:集成的流体和数据包网络模拟

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摘要

A number of methods exist that can be used to create simulation models for measuring the performance of computer networks. The most commonly used method is packet level simulation, which models the detailed behavior of every packet in the network, and results in a highly accurate picture of overall network behavior. A less frequently used, but sometimes more computationally efficient, method is the fluid model approach. In this method, aggregations of flows are modeled as fluid flowing through pipes, and queues are modeled as fixed capacity buckets. The buckets are connected via pipes, where the maximum allowable flow rate of fluid in the pipes represents the bandwidth of the communication links being modeled. Fluid models generally result in a less accurate picture of the network's behavior since they rely on aggregation of flows and ignore actions specific to individual flows. We introduce a new hybrid simulation environment that leverages the strong points of each of these two modeling methods. Our hybrid method uses fluid models to represent aggregations of flows for which less detail is required, and packet models to represent individual flows for which more detail is needed. The result is a computationally efficient simulation model that results in a high level of accuracy and detail in some of the flows, while abstracting away details of other flows. We show a computational speedup of more than twenty in some cases, with little reduction in accuracy of the simulation results.
机译:存在许多方法,可用于创建用于测量计算机网络性能的仿真模型。最常用的方法是分组级仿真,它模拟了网络中每个数据包的详细行为,并导致高度准确的整体网络行为图像。频繁使用的较不常用,但有时更加计算效率,方法是流体模型方法。在该方法中,流的聚合被建模为流过管道的流体,并且队列被建模为固定容量桶。铲斗通过管道连接,其中管道中的流体的最大允许流速表示被建模的通信链路的带宽。流体模型通常导致网络行为的更易于准确的图片,因为它们依赖流量的聚合并忽略特定于各个流的动作。我们介绍了一种新的混合模拟环境,可以利用这两个建模方法中的每一个的强点。我们的混合方法使用流体模型来表示需要更少细节的流的聚合,以及表示需要更多细节的单独流的分组模型。结果是计算上有效的仿真模型,导致一些流动中的高度精度和细节,同时抽象了其他流的细节。我们在某些情况下显示了超过二十的计算加速,仿真结果的准确性几乎没有降低。

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