A Power-Efficient Approach to TCAM-Based Regular Expression Matching
Kun Huang, Xuelin Chen · 2018
Ternary content addressable memories (TCAMs) have been used to implement high-speed regular expression (Regex) matching for deep packet inspection. However, one major drawback of TCAMs is their high power consumption, which is becoming critical with the increasing number of Regex patterns. In this paper, we present GreenCAM, a power-efficient approach to TCAM-based Regex matching for reducing the power consump-tion of TCAMs. We introduce a simple yet effective idea of sepa-rating input characters from states in TCAMs to develop a three-stage architecture for low-power Regex matching. For this archi-tecture, we propose two techniques of character indexing and table partitioning to minimize the number of TCAM blocks acti-vated for each transition lookup in average and worst cases. Ex-periments on real Regex pattern sets show that GreenCAM re-quires only two active TCAM blocks per transition lookup on average, and achieves significant power reductions of up to sever-al orders of magnitude as well as higher matching throughput compared to previous schemes.