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A space- and power-efficient multi-match packet classification technique combining TCAMs and SRAMs

机译:结合了TCAM和SRAM的节省空间和功率的多重匹配数据包分类技术

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摘要

Packet classification is implemented in modern network routers for providing differentiated services based on packet header information. Traditional packet classification only reports a single matched rule with the highest priority for an incoming packet and takes an action accordingly. With the emergence of new Internet applications such as network intrusion detection system, all matched rules need to be reported. This multi-match problem is more challenging and is attracting attentions in recent years. Because of the stringent time budget on classification, architectural solutions using ternary content addressable memory (TCAM) are the preferred choice for backbone network routers. However, despite its advantage on search speed, TCAM is much more expensive than SRAM, and is notorious for its extraordinarily high power consumption. These problems limit the application and scalability of TCAM-based solutions. This paper presents a tree-based multi-match packet classification technique combining the benefits of both TCAMs and SRAMs. The experiments show that the proposed solution achieves significantly more savings on both memory space and power consumption on packet matching compared to existing solutions.
机译:数据包分类在现代网络路由器中实现,用于基于数据包头信息提供差异化​​服务。传统的数据包分类仅报告输入数据包具有最高优先级的单个匹配规则,并相应地采取措施。随着新的Internet应用程序(如网络入侵检测系统)的出现,需要报告所有匹配的规则。这个多重比赛问题更具挑战性,并且近年来引起了人们的关注。由于严格的分类时间预算,使用三态内容可寻址存储器(TCAM)的体系结构解决方案是骨干网络路由器的首选。但是,尽管TCAM在搜索速度上有优势,但它比SRAM贵得多,并且因其极高的功耗而臭名昭著。这些问题限制了基于TCAM的解决方案的应用和可伸缩性。本文提出了一种基于树的多匹配数据包分类技术,结合了TCAM和SRAM的优势。实验表明,与现有解决方案相比,所提出的解决方案在存储空间和数据包匹配功耗方面均实现了明显更多的节省。

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