估算滑动窗口上数据流中活动流的数量

Éric Fusy, F. Giroire
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引用次数: 50

摘要

引入了一种新的算法来估计数据流中不同流(或连接)的数量。该算法保持对滑动窗口上不同流的数量的准确估计。它很容易实现,最优地并行化,并且在辅助内存和估计精度之间有很好的权衡:1/√m阶的相对精度本质上需要mln(n/m)个单词的内存,其中n是在滑动窗口上看到的流数量的上限。例如,对于具有数百万流的流,仅64kB的内存就足以维持大约4%的估计精度。通过仿真和实际交通实验验证了该算法的有效性。它被证明是非常有效的监控流量和检测攻击。
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Estimating the Number of Active Flows in a Data Stream over a Sliding Window
A new algorithm is introduced to estimate the number of distinct flows (or connections) in a data stream. The algorithm maintains an accurate estimate of the number of distinct flows over a sliding window. It is simple to implement, parallelizes optimally, and has a very good trade-off between auxiliary memory and accuracy of the estimate: a relative accuracy of order 1/√m requires essentially a memory of order mln(n/m) words, where n is an upper bound on the number of flows to be seen over the sliding window. For instance, a memory of only 64kB is sufficient to maintain an estimate with accuracy of order 4 percents for a stream with several million flows. The algorithm has been validated both by simulations and experimentations on real traffic. It proves very efficient to monitor traffic and detect attacks.
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