Packet classification using multidimensional cutting

This paper introduces a classification algorithm called phHyperCuts. Like the previously best known algorithm, HiCuts, HyperCuts is based on a decision tree structure. Unlike HiCuts, however, in which each node in the decision tree represents a hyperplane, each node in the HyperCuts decision tree represents a k--dimensional hypercube. Using this extra degree of freedom and a new set of heuristics to find optimal hypercubes for a given amount of storage, HyperCuts can provide an order of magnitude improvement over existing classification algorithms. HyperCuts uses 2 to 10 times less memory than HiCuts optimized for memory, while the worst case search time of HyperCuts is 50--500% better than that of HiCuts optimized for speed. Compared with another recent scheme, EGT-PC, HyperCuts uses 1.8--7 times less memory space while the worst case search time is up to 5 times smaller. More importantly, unlike EGT-PC, HyperCuts can be fully pipelined to provide one classification result every packet arrival time, and also allows fast updates.

[1]  Svante Carlsson,et al.  Small forwarding tables for fast routing lookups , 1997, SIGCOMM '97.

[2]  T. V. Lakshman,et al.  High-speed policy-based packet forwarding using efficient multi-dimensional range matching , 1998, SIGCOMM '98.

[3]  George Varghese,et al.  Fast and scalable layer four switching , 1998, SIGCOMM '98.

[4]  Venkatachary Srinivasan,et al.  Packet classification using tuple space search , 1999, SIGCOMM '99.

[5]  Nick McKeown,et al.  Packet classification on multiple fields , 1999, SIGCOMM '99.

[6]  Pankaj Gupta,et al.  Packet Classification using Hierarchical Intelligent Cuttings , 1999 .

[7]  Subhash Suri,et al.  Space Decomposition Techniques for Fast Layer-4 Switching , 1999, Protocols for High-Speed Networks.

[8]  Thomas Y. C. Woo A modular approach to packet classification: algorithms and results , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[9]  Anja Feldmann,et al.  Tradeoffs for packet classification , 2000, Proceedings IEEE INFOCOM 2000. Conference on Computer Communications. Nineteenth Annual Joint Conference of the IEEE Computer and Communications Societies (Cat. No.00CH37064).

[10]  George Varghese,et al.  Fast firewall implementations for software and hardware-based routers , 2001, Proceedings Ninth International Conference on Network Protocols. ICNP 2001.

[11]  George Varghese,et al.  Packet classification for core routers: is there an alternative to CAMs? , 2003, IEEE INFOCOM 2003. Twenty-second Annual Joint Conference of the IEEE Computer and Communications Societies (IEEE Cat. No.03CH37428).

[12]  George Varghese,et al.  Scalable packet classification , 2001, SIGCOMM '01.