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Extensions to decision-tree based packet classification algorithms to address new classification paradigms

机译:扩展基于决策树的分组分类算法,以解决新的分类范式

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摘要

The decision-tree based packet-classification algorithm field has seen many contributions since the first algorithm using a geometrical rule representation, HiCuts, has been proposed. While hardware reported implementations for this class of algorithms have proven that a high throughput can be reached, those algorithms are inherently facing a tradeoff between speed and memory consumption.
机译:自从提出了第一个使用几何规则表示法HiCuts的算法以来,基于决策树的数据包分类算法领域就做出了许多贡献。虽然硬件报告的此类算法的实现已证明可以实现高吞吐量,但这些算法固有地面临速度和内存消耗之间的权衡。

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