Publication detail

Fast and scalable packet classification using perfect hash functions

PUŠ, V. KOŘENEK, J.

Original Title

Fast and scalable packet classification using perfect hash functions

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

Packet classification is an important operation for applications such as routers, firewalls or intrusion detection systems. Many algorithms and hardware architectures for packet classification have been created, but none of them can compete with the speed of TCAMs in the worst case. We propose new hardware-based algorithm for packet classification. The solution is based on problem decomposition and is aimed at the highest network speeds. A unique property of the algorithm is the constant time complexity in terms of external memory accesses. The algorithm performs exactly two external memory accesses to classify a packet. Using FPGA and one commodity SRAM chip, a throughput of 150 million packets per second can be achieved. This makes throughput of 100 Gbps for the shortest packets. Further performance scaling is possible with more or faster SRAM chips.

Keywords

classification, FPGA, perfect hash function

Authors

PUŠ, V.; KOŘENEK, J.

RIV year

2009

Released

28. 5. 2009

Publisher

Association for Computing Machinery

Location

New York

ISBN

978-1-60558-410-2

Book

Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays

Edition

Association for Computing Machinery

Pages from

229

Pages to

236

Pages count

8

URL

https://www.fit.vut.cz/research/publication/8952/

BibTex

@inproceedings{BUT33726,
  author="Viktor {Puš} and Jan {Kořenek}",
  title="Fast and scalable packet classification using perfect hash functions",
  booktitle="Proceeding of the ACM/SIGDA international symposium on Field programmable gate arrays",
  year="2009",
  series="Association for Computing Machinery",
  pages="229--236",
  publisher="Association for Computing Machinery",
  address="New York",
  isbn="978-1-60558-410-2",
  url="https://www.fit.vut.cz/research/publication/8952/"
}