Fast packet classification using bloom filters

  • Authors:
  • Sarang Dharmapurikar;Haoyu Song;Jonathan Turner;John Lockwood

  • Affiliations:
  • Washington University in St. Louis, St. Louis, MO;Washington University in St. Louis, St. Louis, MO;Washington University in St. Louis, St. Louis, MO;Washington University in St. Louis, St. Louis, MO

  • Venue:
  • Proceedings of the 2006 ACM/IEEE symposium on Architecture for networking and communications systems
  • Year:
  • 2006

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Abstract

Ternary Content Addressable Memory (TCAM), although widely used for general packet classification, is an expensive and high power-consuming device. Algorithmic solutions which rely on commodity memory chips are relatively inexpensive and power-efficient but have not been able to match the generality and performance of TCAMs. Therefore, the development of fast and power-efficient algorithmic packet classification techniques continues to be a research subject.In this paper we propose a new approach to packet classification which combines architectural and algorithmic techniques. Our starting point is the well-known crossproduct algorithm which is fast but has significant memory overhead due to the extra rules needed to represent the crossproducts. We show how to modify the crossproduct method in a way that drastically reduces the memory requirement without compromising on performance. Unnecessary accesses to the off-chip memory are avoided by filtering them through on-chip Bloom filters. For packets that match p rules in a rule set, our algorithm requires just 4 + p + ε independent memory accesses to return all matching rules, where ε