Detail publikace

Multiobjective Evolution of Hash Functions for High Speed Networks

GROCHOL, D. SEKANINA, L.

Originální název

Multiobjective Evolution of Hash Functions for High Speed Networks

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

Hashing is a critical function in capturing and analysis of network flows as its quality and execution time influences the maximum throughput of network monitoring devices. In this paper, we propose a multi-objective linear genetic programming approach to evolve fast and high-quality hash functions for common processors. The search algorithm simultaneously optimizes the quality of hashing and the execution time. As it is very time consuming to obtain the real execution time for a candidate solution on a particular processor, the execution time is estimated in the fitness function. In order to demonstrate the superiority of the proposed approach, evolved hash functions are compared with hash functions available in the literature using real-world network data.

Klíčová slova

NSGA-II, linear genetic programming, hash function, network

Autoři

GROCHOL, D.; SEKANINA, L.

Vydáno

5. 6. 2017

Nakladatel

IEEE Computer Society

Místo

San Sebastian

ISBN

978-1-5090-4600-3

Kniha

Proceedings of the 2017 IEEE Congress on Evolutionary Computation

Strany od

1533

Strany do

1540

Strany počet

8

URL

https://www.fit.vut.cz/research/publication/11325/

BibTex

@inproceedings{BUT144407,
  author="David {Grochol} and Lukáš {Sekanina}",
  title="Multiobjective Evolution of Hash Functions for High Speed Networks",
  booktitle="Proceedings of the 2017 IEEE Congress on Evolutionary Computation",
  year="2017",
  pages="1533--1540",
  publisher="IEEE Computer Society",
  address="San Sebastian",
  doi="10.1109/CEC.2017.7969485",
  isbn="978-1-5090-4600-3",
  url="https://www.fit.vut.cz/research/publication/11325/"
}

Dokumenty

E-17352.pdf