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首页> 外文期刊>IEEE/ACM Transactions on Networking >TCAM-Based Multi-Match Packet Classification Using Multidimensional Rule Layering
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TCAM-Based Multi-Match Packet Classification Using Multidimensional Rule Layering

机译:使用多维规则分层的基于TCAM的多匹配数据包分类

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Ternary content addressable memory (TCAM) has superior performance for single-match packet classification but not the case for multi-match packet classification. The limitation is caused by TCAM architecture that reports only the first matching rule. To cope with the limitation, previous algorithms use extra TCAM entries or accesses, or both, to fulfill multi-match packet classification. These algorithms also reorder rules; thus, a multi-match classifier based on these algorithms cannot maintain performance for single-match packet classification. In other words, all matching rules must be yielded to determine the highest priority matching rule. In this paper, we present a TCAM-based scheme for multi-match packet classification without single-match penalty. Our scheme partitions a rule set based on range layering, which can be applied to achieve range encoding. The rule partitioning generates rule subsets which satisfy that the rules in a subset are mutually disjoint. Each rule is then tagged a bitmap for subset identification to fulfill multi-match packet classification. Two approaches, loose coupling and tight coupling, are derived with different search procedures while incorporating range encoding. Both approaches can maintain original rule order, but with different performance tradeoff. We also present a refinement which uses all available TCAM entries to improve the performance of multi-match packet classification. The experimental results show that combining range encoding with multi-match packet classification has advantages of storage efficiency and speed superiority. The capability of supporting single-match packet classification also provides better flexibility of applying different packet actions.
机译:三元内容可寻址存储器(TCAM)在单匹配数据包分类中具有出色的性能,而在多匹配数据包分类中则没有。该限制是由仅报告第一个匹配规则的TCAM体系结构引起的。为了解决该限制,先前的算法使用额外的TCAM条目或访问或两者,以实现多匹配数据包分类。这些算法还会对规则进行重新排序。因此,基于这些算法的多匹配分类器无法维持单匹配包分类的性能。换句话说,必须产生所有匹配规则以确定最高优先级匹配规则。在本文中,我们提出了一种基于TCAM的多匹配数据包分类方案,而没有单匹配损失。我们的方案基于范围分层对规则集进行分区,可以将其应用于实现范围编码。规则分区生成规则子集,该子集满足子集中的规则互不相交的情况。然后为每个规则标记一个位图,以进行子集标识,以实现多匹配数据包分类。在合并范围编码的同时,使用不同的搜索过程可以得出松耦合和紧耦合两种方法。两种方法都可以维持原始规则顺序,但具有不同的性能折衷。我们还提出了一种改进方案,它使用所有可用的TCAM条目来提高多匹配数据包分类的性能。实验结果表明,将范围编码与多匹配包分类相结合具有存储效率和速度优势的优点。支持单匹配包分类的功能还为应用不同的包操作提供了更好的灵活性。

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