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Structural compression of packet classification trees

Published: 29 October 2012 Publication History

Abstract

Most of state-of-the-art packet classification algorithms employ heuristics to trade off between classification speed and memory usage. However, intelligent heuristics often result in complex data structures in algorithm implementation. This brings difficulties to the deployment and optimization of packet classification algorithms. In this poster, a structural compression approach is presented for decision tree based packet classification algorithms. This approach exploits the similarity in real-life filter sets to achieve high compression ratio without loss of tree semantics.

References

[1]
P. Gupta and N. McKeown. "Classifying Packets with Hierarchical Intelligent Cuttings," in IEEE Micro, 2000.
[2]
Y. Qi, L. Xu, B. Yang, Y. Xue and J. Li. "Packet Clas-sification Algorithms: From Theory to Practice," in Proc. of INFOCOM, 2009.
[3]
Y. Qi, B. Xu, F. He, B. Yang, J. Yu and J. Li. "Towards High-performance Flow-level Packet Processing on Multi-core Network Processors," in Proc. of ANCS, 2007.
[4]
ClassBench: A Packet Classification Benchmark. http://www.arl.wustl.edu/classbench/
[5]
B. Vamanan, G. Voskuilen and T. Vijaykumar. "Effi-Cuts: Optimizing Packet Classification for Memory and Throughput," in Proc. of SIGCOMM, 2010.
[6]
J. Fong, Y. Qi, J. Li and W. Jiang. "ParaSplit: A Scalable Architecture on FPGA for Terabit Packet Classification," in Proc. of HOTI, 2012.

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  1. Structural compression of packet classification trees

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      cover image ACM Conferences
      ANCS '12: Proceedings of the eighth ACM/IEEE symposium on Architectures for networking and communications systems
      October 2012
      270 pages
      ISBN:9781450316859
      DOI:10.1145/2396556

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 29 October 2012

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      Author Tags

      1. algorithms
      2. data structure
      3. packet classification

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