MagicTCAM:一个快速TCAM更新的多TCAM方案

Ruyi Yao, Cong Luo, Xuandong Liu, Ying Wan, B. Liu, Wen J. Li, Yang Xu
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引用次数: 6

摘要

三元内容可寻址存储器(TCAM)是软件定义网络(SDN)中用于高速流表查找的一种流行解决方案。在TCAM中插入规则是一项耗时的操作。为了确保语义的正确性,必须将重叠的规则按优先级递减的顺序存储在TCAM中,并且可能需要许多规则移动来为单个插入的规则腾出空间。当进行规则插入时,将暂停常规流表查找,这可能导致SDN应用程序的用户体验下降。在本文中,我们提出了一个名为MagicTCAM的多tcam框架来减少规则插入过程中的规则移动。MagicTCAM的核心在于三个操作:分层、分区和旋转。通过分层,重叠最少的规则将被分组(即分层)到子规则集中。因此,规则移动的数量大大减少,因为子规则集中的大多数规则是不重叠的。为了实现tcam中的负载均衡,将每个子规则集中的规则进一步划分,并以旋转的方式分配到不同的tcam中。此外,提出了一种跨tcam移动算法,允许规则在tcam之间移动,以减少规则的移动。实验结果表明,对于两个半尺寸的tcam, MagicTCAM与目前的工作相比,平均减少了39%的规则运动,计算时间也缩短了一半。
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MagicTCAM: A Multiple-TCAM Scheme for Fast TCAM Update
Ternary Content-Addressable Memory (TCAM) is a popular solution for high-speed flow table lookup in Software-Defined Networking (SDN). Rule insertion in TCAM is a time-consuming operation. To ensure semantic correctness, rules overlapped must be stored in TCAM with decreasing priority order and many rule movements may be needed to make space for a single inserted rule. When a rule insertion is in progress, the regular flow table lookup will be suspended, which could lead to a degraded user experience for SDN applications. In this paper, we propose a multiple-TCAM framework named MagicTCAM to reduce the rule movements during a rule insertion. The core of MagicTCAM lies in three operations: layering, partitioning and rotating. By layering, rules with the least overlapping will be grouped (i.e., layered) into a sub-ruleset. The number of rule movements is therefore greatly reduced as most of rules in a sub-ruleset are non-overlapped. To achieve balanced load in TCAMs, rules in each sub-ruleset are further partitioned and dispatched into different TCAMs in a rotating manner. In addition, an inter-TCAM movement algorithm is proposed to allow rules to be moved between TCAMs for reduced rule movement. Experiment results show that with two half-sized TCAMs, MagicTCAM reduces the rule movements by 39% on average compared with the state-of-the-art work while the computation time is shortened by half as well.
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