Evolutionary circuit design for fast FPGA-based classification of network application protocols

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "D. Grochol and L. Sekanina and M. Zadnik and 
                 J. Korenek and V. Kosar",
  title =        "Evolutionary circuit design for fast FPGA-based
                 classification of network application protocols",
  journal =      "Applied Soft Computing",
  volume =       "38",
  pages =        "933--941",
  year =         "2016",
  ISSN =         "1568-4946",
  DOI =          "doi:10.1016/j.asoc.2015.09.046",
  URL =          "http://www.sciencedirect.com/science/article/pii/S1568494615006262",
  abstract =     "The evolutionary design can produce fast and efficient
                 implementations of digital circuits. It is shown in
                 this paper how evolved circuits, optimized for the
                 latency and area, can increase the throughput of a
                 manually designed classifier of application protocols.
                 The classifier is intended for high speed networks
                 operating at 100 Gbps. Because a very low latency is
                 the main design constraint, the classifier is
                 constructed as a combinational circuit in a field
                 programmable gate array (FPGA). The classification is
                 performed using the first packet carrying the
                 application payload. The improvements in latency (and
                 area) obtained by Cartesian genetic programming are
                 validated using a professional FPGA design tool. The
                 quality of classification is evaluated by means of real
                 network data. All results are compared with commonly
                 used classifiers based on regular expressions
                 describing application protocols.",
  keywords =     "genetic algorithms, genetic programming, Application
                 protocol, Classifier, Field programmable gate array",

Genetic Programming entries for David Grochol Lukas Sekanina Martin Zadnik Jan Korenek V Kosar