摘要: 基于三态内容可寻址内存(TCAM)的包分类方法不能有效解决区间膨胀的问题。为此,提出一种有效包分类方法。对包分类规则集中各个域的不同区间进行分组,利用Shadow Encoding方法对同一分组中的所有区间进行重新编码,依据重新编码的区间结果改写原始规则集。实验结果表明,该方法可以平均压缩75.90%的TCAM存储空间。
关键词:
包分类,
三态内容可寻址内存,
区间膨胀,
区间分组,
区间编码,
流水线匹配
Abstract: Ternary Content Addressable Memory(TCAM)-based packet classification methods suffer from the range expansion problem. In this paper, an efficient range encoding method to solve this problem is proposed. It divides all the unique ranges in each field of rules into different groups, and uses the shadow encoding method to re-encode them, rewrites the original rule set according to re-encoding ranges. Experimental results show that this method can reduce TCAM storage space by 75.90% on average.
Key words:
packet classification,
Ternary Content Addressable Memory(TCAM),
range expansion,
range grouping,
range encoding,
pipeline matching
中图分类号:
杨迪. 一种基于TCAM的有效包分类方法[J]. 计算机工程, 2012, 38(21): 283-285,289.
YANG Di. An Efficient Packet Classification Method Based on TCAM[J]. Computer Engineering, 2012, 38(21): 283-285,289.