一种基于Bloom-filter表项压缩的TCAM业务识别算法

A TCAM Service Identification Algorithm Based on Access Compression Using Bloom-filter

在三态内容寻址存储器(Ternary Content Addressable Memory,TCAM)表项宽度和存储容量约束下,该文提出一种基于匹配表项压缩的BF-TCAM算法,采用Bloom-Filter(BF)对匹配关键字进行单字节编码压缩关键字长度,解决了匹配吞吐率低和存储空间不足问题。针对BF在表项压缩过程带来的冲突率上升问题,引入向量存储空间策略,利用向量存储空间实现多个哈希函数映射,相对于比特向量策略,有利于降低匹配冲突率。测试实验表明,相对于传统的TCAM匹配算法,BF-TCAM算法不但提高了匹配吞吐率和存储空间利用率,同时可有效降低BF压缩产生的冲突率。

Within the confines of access width and storage capacity in Ternary Content Addressable Memory（TCAM） chip,pattern matching algorithm using TCAM has low throughput and limited memory.This paper proposes BF-TCAM algorithm based on access compression by single byte coding using Bloom-Filter（BF） algorithm,increases the throughput and improves the utilization efficiency of storage space.BF algorithm will bring collision,which can be reduced by using vector memory instead of bit vector in BF-TCAM algorithm.The experimentation shows that the BF-TCAM algorithm proposed in this paper can improve the matching throughput and storage space utilization,and at the same time,effectively reduce the conflict ratio resulting from BF compression.