On the Intrinsic Fault-Tolerance Nature of Parallel Genetic Programming

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{DBLP:conf/pdp/GonzalezV07,
  author =       "Daniel Lombrana Gonzalez and 
                 Francisco {Fernandez de Vega}",
  title =        "On the Intrinsic Fault-Tolerance Nature of Parallel
                 Genetic Programming",
  booktitle =    "15th Euromicro Conference on Parallel, Distributed and
                 Network-based Processing",
  year =         "2007",
  editor =       "Pasqua D'Ambra and Mario R. Guarracino",
  pages =        "450--458",
  bibsource =    "DBLP, http://dblp.uni-trier.de",
  address =      "Naples",
  month =        "7-9 " # feb,
  publisher =    "IEEE",
  keywords =     "genetic algorithms, genetic programming, fault
                 tolerance, parallel genetic programming",
  ISBN =         "0-7695-2784-1",
  ISSN =         "1066-6192",
  DOI =          "doi:10.1109/PDP.2007.56",
  abstract =     "In this paper we show how Parallel Genetic Programming
                 can run on a distributed system with volatile resources
                 without any lack of efficiency. By means of a series of
                 experiments, we test whether Parallel GP -and
                 consistently Evolutionary Algorithms- are intrinsically
                 fault-tolerant. The interest of this result is crucial
                 for researchers dealing with real-life problems in
                 which parallel and distributed systems are required for
                 obtaining results on a reasonable time. In that case,
                 parallel GP tools will not require the inclusion of
                 fault-tolerant computing techniques or libraries when
                 running on Meta-systems undergoing volatility, such us
                 Desktop Grids offering Public Resource Computing. We
                 test the performance of the algorithm by studying the
                 quality of solutions when running over distributed
                 resources undergoing processors failures, when compared
                 with a fault-free environment. This new feature, which
                 shows its advantages, improves the dependability of the
                 Parallel Genetic Programming Algorithm.",
  notes =        "PDP 2007 http://www.na.icar.cnr.it/~pdp2007",
}

Genetic Programming entries for Daniel Lombrana Gonzalez Rodriguez Francisco Fernandez de Vega

Citations