NDLI: TCAM Razor: A Systematic Approach Towards Minimizing Packet Classifiers in TCAMs

Content Provider	IEEE Xplore Digital Library
Author	Meiners, C.R. Liu, A.X. Torng, E.
Copyright Year	2007
Description	Author affiliation: Michigan State Univ., East Lansing (Meiners, C.R.; Liu, A.X.; Torng, E.)
Abstract	Packet classification is the core mechanism that enables many networking services on the Internet such as firewall packet filtering and traffic accounting. Using ternary content addressable memories (TCAMs) to perform high-speed packet classification has become the de facto standard in industry. TCAMs classify packets in constant time by comparing a packet with all classification rules of ternary encoding in parallel. Despite their high speed, TCAMs suffer from the well-known range expansion problem. As packet classification rules usually have fields specified as ranges, converting such rules to TCAM-compatible rules may result in an explosive increase in the number of rules. This is not a problem if TCAMs have large capacities. Unfortunately, TCAMs have very limited capacity, and more rules means more power consumption and more heat generation for TCAMs. Even worse, the number of rules in packet classifiers have been increasing rapidly with the growing number of services deployed on the internet. To address the range expansion problem of TCAMs, we consider the following problem: given a packet classifier, how can we generate another semantically equivalent packet classifier that requires the least number of TCAM entries? In this paper, we propose a systematic approach, the TCAM Razor, that is effective, efficient, and practical. In terms of effectiveness, our TCAM Razor prototype achieves a total compression ratio of 3.9%, which is significantly better than the previously published best result of 54%. In terms of efficiency, our TCAM Razor prototype runs in seconds, even for large packet classifiers. Finally, in terms of practicality, our TCAM Razor approach can be easily deployed as it does not require any modification to existing packet classification systems, unlike many previous range expansion solutions.
Starting Page	266
Ending Page	275
File Size	2469956
Page Count	10
File Format	PDF
ISBN	9781424415878
DOI	10.1109/ICNP.2007.4375857
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-10-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Web and internet services Prototypes IP networks Information filtering Information filters Telecommunication traffic Associative memory Encoding Explosives Energy consumption
Content Type	Text
Resource Type	Article

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