Efficient Mapping of Range Classifier into Ternary-CAM
HOTI '02 Proceedings of the 10th Symposium on High Performance Interconnects HOT Interconnects
Packet classification using multidimensional cutting
Proceedings of the 2003 conference on Applications, technologies, architectures, and protocols for computer communications
Packet Classification Using Extended TCAMs
ICNP '03 Proceedings of the 11th IEEE International Conference on Network Protocols
Algorithms for advanced packet classification with ternary CAMs
Proceedings of the 2005 conference on Applications, technologies, architectures, and protocols for computer communications
Packet classifiers in ternary CAMs can be smaller
SIGMETRICS '06/Performance '06 Proceedings of the joint international conference on Measurement and modeling of computer systems
Compressing rectilinear pictures and minimizing access control lists
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Fast and scalable packet classification
IEEE Journal on Selected Areas in Communications
Algorithms for packet classification
IEEE Network: The Magazine of Global Internetworking
Bidirectional range extension for TCAM-based packet classification
NETWORKING'10 Proceedings of the 9th IFIP TC 6 international conference on Networking
A prefix-based approach for managing hybrid specifications in complex packet filtering
Computer Networks: The International Journal of Computer and Telecommunications Networking
Managing hybrid packet filter's specifications
International Journal of Security and Networks
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Packet classification is a fundamental task for network devices such as edge routers, firewalls, and intrusion detection systems. Currently, most vendors use Ternary Content Addressable Memories (TCAMs) to achieve high-performance packet classification. TCAMs use parallel hardware to check all rules simultaneously. Despite their high speed, TCAMs have a fundamental in dealing with ranges efficiently. Many packet classification rules contain range specifications, each of which needs to be translated into multiple prefixes to store in TCAMs. Such translation may result in an explosive increase in the number of required TCAM entries. In this paper, we propose a redundancy removal algorithm using a tree representation of rules. The proposed algorithm removes redundant rules and combines overlaying rules to build an equivalent, smaller rule set for a given packet classifier. This equivalent transformation can significantly reduce the number of required TCAM entries. Our experiments show a reduction of 70.9% in the number of TCAM entries. Besides, our algorithm eliminates requirement of priority encoder circuits. It can also be used as a preprocessor, in tandem with other methods, to achieve further performance imrpovement.