Evolutionary Design of Fast High-quality Hash Functions for Network Applications
Created by W.Langdon from
gp-bibliography.bib Revision:1.8051
- @InProceedings{Grochol:2016:GECCO,
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author = "David Grochol and Lukas Sekanina",
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title = "Evolutionary Design of Fast High-quality Hash
Functions for Network Applications",
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booktitle = "GECCO '16: Proceedings of the 2016 Annual Conference
on Genetic and Evolutionary Computation",
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year = "2016",
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editor = "Tobias Friedrich and Frank Neumann and
Andrew M. Sutton and Martin Middendorf and Xiaodong Li and
Emma Hart and Mengjie Zhang and Youhei Akimoto and
Peter A. N. Bosman and Terry Soule and Risto Miikkulainen and
Daniele Loiacono and Julian Togelius and
Manuel Lopez-Ibanez and Holger Hoos and Julia Handl and
Faustino Gomez and Carlos M. Fonseca and
Heike Trautmann and Alberto Moraglio and William F. Punch and
Krzysztof Krawiec and Zdenek Vasicek and
Thomas Jansen and Jim Smith and Simone Ludwig and JJ Merelo and
Boris Naujoks and Enrique Alba and Gabriela Ochoa and
Simon Poulding and Dirk Sudholt and Timo Koetzing",
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pages = "901--908",
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keywords = "genetic algorithms, genetic programming",
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month = "20-24 " # jul,
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organisation = "SIGEVO",
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address = "Denver, USA",
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publisher = "ACM",
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publisher_address = "New York, NY, USA",
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isbn13 = "978-1-4503-4206-3",
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DOI = "doi:10.1145/2908812.2908825",
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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.",
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notes = "GECCO-2016 A Recombination of the 25th International
Conference on Genetic Algorithms (ICGA-2016) and the
21st Annual Genetic Programming Conference (GP-2016)",
- }
Genetic Programming entries for
David Grochol
Lukas Sekanina
Citations