使用位压缩快速分组分类

Chia-Jen Hsu, Chien Chen, Chun-Yuan Lin
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引用次数: 5

摘要

为了支持互联网安全、虚拟专用网、QoS等,互联网路由器需要将进入的数据包快速分类为流。报文分类器使用报文头中包含的信息和路由器中预定义的规则表对报文进行分类。本文提出了一种新的分组分类算法——位压缩算法。与之前最著名的位图交叉算法一样,位压缩基于多维范围查找方法。由于位图交叉点的位向量包含大量的“0”位,因此位向量可以被压缩。我们通过保留有用的信息来压缩位向量,但去掉位向量中多余的“0”位。此外,通配符规则还支持更广泛的改进。与位图相交算法相比,位压缩算法在平均情况下将存储复杂度从theta (dN2)降低到theta (dN-logN),其中d表示维数,N表示规则数。通过探索内存层次结构,我们发现在Intel IXP1200网络处理器上,位压缩算法比位图交叉算法需要更少的内存访问。由于内存访问占查找时间的主导地位,尽管位压缩方案需要额外的解压时间,但平均而言,位压缩方案在分类性能上仍然优于位图交叉方案
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Fast packet classification using bit compression
In order to support Internet security, virtual private networks, QoS, etc., Internet routers need to classify incoming packets quickly into flows. A packet classifier uses information contained in the packet header and a predefined rule table in the routers to classify the packets. This paper presents a novel packet classification algorithm, called the bit compression algorithm. Like the previously best known algorithm, bitmap intersection, bit compression is based on the multiple dimensional range lookup approach. Since the bit vectors of the bitmap intersection contain lots of '0' bits, the bit vectors could be compressed. We compress the bit vectors by preserving useful information but removing the redundant '0' bits of the bit vectors. Additionally, the wildcard rules also enable more extensive improvement. Comparing with the bitmap intersection algorithm, the bit compression algorithm reduces the storage complexity in the average-case from thetas (dN2) to thetas (dN-logN), where d denotes the number of dimensions and N represents the number of rules. By exploring the memory hierarchy, we show that bit compression algorithm requires much less memory access than bitmap intersection algorithm on Intel IXP1200 network processor. Since memory access dominates the lookup time, even though extra decompression time is required for bit compression scheme, the bit compression scheme in the average still outperforms bitmap intersection scheme on the classification performance
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