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Hybrid sampling for estimating flow size distribution and its implementation

机译:混合采样估计流量分布及其实现

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Recently, it has been necessary to perform traffic sampling in order to deteriorate the load of capturing and analyzing processes, as the amount of ISP traffic grows. Packet sampling and flow sampling are main sampling techniques. In order to estimate flow size distribution from sampled data, each sampling method has its own advantages and disadvantages. Flow sampling can extract flows in proportion to the original flow size distribution but is difficult to extract large-sized flows due to the heavy-tailed flow size distribution. On the other hand, packet sampling can extract large-sized flows but complete flows cannot be extracted. In this paper, we propose a hybrid sampling method which performs both flow sampling and packet sampling in parallel to utilize both advantages of above two methods and improve estimation accuracy. We also propose cost-effective implementation which employs a general-purpose switch. By verifying with real traffic data, we confirmed the effectiveness of our proposed method in terms of reproducibility.
机译:最近,有必要执行流量采样,以便恶化捕获和分析过程的负荷,因为ISP流量的增加。数据包采样和流采样是主要采样技术。为了估计从采样数据的流量尺寸分布,每个采样方法都具有其自身的优点和缺点。流动采样可以与原始流量尺寸分布成比例的流动,但由于重尾流量分布,难以提取大型流动。另一方面,数据包采样可以提取大型流动但无法提取完整的流量。在本文中,我们提出了一种混合采样方法,该方法并联执行流采样和分组采样,以利用两种方法的两种优点,提高估计精度。我们还提出了具有通用交换机的经济效益的实施。通过使用实际交通数据验证,我们在再现性方面确认了我们提出的方法的有效性。

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