基于空间节省算法的层次化Heavy Hitter
Hierarchical Heavy Hitters with the Space Saving Algorithm
摘要：
分层重命中问题将频繁项的概念扩展到按层次结构排列的数据。这个问题已经应用到网络流量监控，异常检测和DDoS检测。我们提出了一个新的流式近似算法计算层次重打击，有几个优点比以前的算法。它改善了早期算法的最坏情况下的时间和空间界限，概念上简单，更容易实现，提供了更好的精度保证，很容易采用分布式或并行设置，并可以有效地实现在商品硬件，如三进制内容可寻址存储器（TCAM）。我们目前的实验结果表明，对于主要的实际利益的参数，我们的二维算法是优于现有的算法在速度和精度方面，在空间方面的竞争力，而我们的一维算法也优于在速度和精度更有限的参数范围。
英文摘要：
The Hierarchical Heavy Hitters problem extends the notion of frequent items to data arranged in a hierarchy. This problem has applications to network traffic monitoring, anomaly detection, and DDoS detection. We present a new streaming approximation algorithm for computing Hierarchical Heavy Hitters that has several advantages over previous algorithms. It improves on the worst-case time and space bounds of earlier algorithms, is conceptually simple and substantially easier to implement, offers improved accuracy guarantees, is easily adopted to a distributed or parallel setting, and can be efficiently implemented in commodity hardware such as ternary content addressable memory (TCAMs). We present experimental results showing that for parameters of primary practical interest, our two-dimensional algorithm is superior to existing algorithms in terms of speed and accuracy, and competitive in terms of space, while our one-dimensional algorithm is also superior in terms of speed and accuracy for a more limited range of parameters.
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