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FastFlow: A Framework for Accurate Characterization of Network Traffic

机译:FastFlow:准确表征网络流量的框架

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This paper proposes a new measurement architecture and associated traffic estimation algorithm called FastFlow that uses the heavy-tailed nature of Internet traffic in order to distinguish packets belonging to short lived flows (SLFs) and long lived flows (LLFs). While complete information is stored for SLFs, only partial information related to LLFs is collected using systematic sampling. The absence of data points in LLFs is approximated using a likelihood function defined over the coupon collector problem and the distribution of underlying traffic estimated using the non-parametric Parzen window technique. We validate the performance of our approach using traffic traces collected from our lab and observe that the estimated statistics match the observed traces with high accuracy.
机译:本文提出了一种新的测量架构和相关的流量估计算法,称为FastFlow,它使用Internet流量的重尾性质,以区分属于短居住的流(SLF)和长寿命流(LLF)。虽然为SLF存储了完整信息,但仅使用系统采样收集与LLF相关的部分信息。使用在优惠券收集器问题上限定的似然函数以及使用非参数栏窗口技术估计的底层流量的分布来近似LLF中的数据点。我们使用从我们实验室收集的流量迹线验证我们的方法的性能,并观察到估计的统计数据匹配高精度的观察到的迹线。

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