Evolutionary design of hash function pairs for network filters

Created by W.Langdon from gp-bibliography.bib Revision:1.8129

@Article{DOBAI2017173,

• author = "Roland Dobai and Jan Korenek and Lukas Sekanina",
• title = "Evolutionary design of hash function pairs for network filters",
• journal = "Applied Soft Computing",
• year = "2017",
• volume = "56",
• number = "Supplement C",
• pages = "173--181",
• month = jul,
• keywords = "genetic algorithms, genetic programming, EHW, Evolutionary algorithm, Hash function, Network filter, Field-programmable gate array, Cuckoo",
• ISSN = "1568-4946",
• URL = "http://www.sciencedirect.com/science/article/pii/S1568494617301321",
• DOI = "doi:10.1016/j.asoc.2017.03.009",
• abstract = "Network filtering is a challenging area in high-speed computer networks, mostly because lots of filtering rules are required and there is only a limited time available for matching these rules. Therefore, network filters accelerated by field-programmable gate arrays (FPGAs) are becoming common where the fast lookup of filtering rules is achieved by the use of hash tables. It is desirable to be able to fill-up these tables efficiently, i.e. to achieve a high table-load factor in order to reduce the offline time of the network filter due to rehashing and/or table replacement. A parallel reconfigurable hash function tuned by an evolutionary algorithm (EA) is proposed in this paper for Internet Protocol (IP) address filtering in FPGAs. The EA fine-tunes the reconfigurable hash function for a given set of IP addresses. The experiments demonstrate that the proposed hash function provides high-speed lookup and achieves a higher table-load factor in comparison with conventional solutions.",
• notes = "Evolvable hardware paper, Not GP?",

}

Genetic Programming entries for Roland Dobai Jan Korenek Lukas Sekanina

Citations