Publication Details

Evolutionary design of fast high-quality hash functions for network applications

GROCHOL, D.; SEKANINA, L. Evolutionary design of fast high-quality hash functions for network applications. In GECCO '16 Proceedings of the 2016 on Genetic and Evolutionary Computation Conference. New York, NY: Association for Computing Machinery, 2016. p. 901-908. ISBN: 978-1-4503-4206-3.
Czech title
Evoluční návrh rychlé a vysoce kvalitní hashovací funkce pro síťové aplikace
Type
conference paper
Language
English
Authors
Grochol David, Ing., Ph.D.
Sekanina Lukáš, prof. Ing., Ph.D. (DCSY)
Keywords

Linear Genetic Programming, Network applications, Hashfunction

Abstract

High speed networks operating at 100 Gbps pose many challenges for hardware and software involved in the packet processing. As the time to process one packet is very short the corresponding operations have to be optimized in terms of the execution time. One of them is non-cryptographic hashing implemented in order to accelerate traffic flow identification. In this paper, a method based on linear genetic programming is presented, which is capable of evolving high-quality hash functions primarily optimized for speed. Evolved hash functions are compared with conventional hash functions in terms of accuracy and execution time using real network data.

Published
2016
Pages
901–908
Proceedings
GECCO '16 Proceedings of the 2016 on Genetic and Evolutionary Computation Conference
Conference
Genetic and Evolutionary Computations Conference 2016, Denver, US
ISBN
978-1-4503-4206-3
Publisher
Association for Computing Machinery
Place
New York, NY
DOI
10.1145/2908812.2908825
UT WoS
000382659200114
EID Scopus
2-s2.0-84985947488
BibTeX 
@inproceedings{BUT130936,
  author="David {Grochol} and Lukáš {Sekanina}",
  title="Evolutionary design of fast high-quality hash functions for network applications",
  booktitle="GECCO '16 Proceedings of the 2016 on Genetic and Evolutionary Computation Conference",
  year="2016",
  pages="901--908",
  publisher="Association for Computing Machinery",
  address="New York, NY",
  doi="10.1145/2908812.2908825",
  isbn="978-1-4503-4206-3",
  url="https://www.fit.vut.cz/research/publication/11078/"
}
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