Customizable execution environments for evolutionary computation using BOINC + virtualization

Created by W.Langdon from gp-bibliography.bib Revision:1.4504

@Article{Fernandez:2013:NC,
  author =       "Francisco {Fernandez de Vega} and Gustavo Olague and 
                 Leonardo Trujillo and Daniel {Lombrana Gonzalez}",
  title =        "Customizable execution environments for evolutionary
                 computation using BOINC + virtualization",
  journal =      "Natural Computing",
  year =         "2013",
  volume =       "12",
  number =       "2",
  pages =        "163--177",
  month =        jun,
  keywords =     "genetic algorithms, genetic programming",
  ISSN =         "1572-9796",
  URL =          "https://doi.org/10.1007/s11047-012-9343-8",
  DOI =          "doi:10.1007/s11047-012-9343-8",
  abstract =     "Evolutionary algorithms (EAs) consume large amounts of
                 computational resources, particularly when they are
                 used to solve real-world problems that require complex
                 fitness evaluations. Beside the lack of resources,
                 scientists face another problem: the absence of the
                 required expertise to adapt applications for parallel
                 and distributed computing models. Moreover, the
                 computing power of PCs is frequently underused at
                 institutions, as desktops are usually devoted to
                 administrative tasks. Therefore, the proposal in this
                 work consists of providing a framework that allows
                 researchers to massively deploy EA experiments by
                 exploiting the computing power of their instituions'
                 PCs by setting up a Desktop Grid System based on the
                 BOINC middleware. This paper presents a new model for
                 running unmodified applications within BOINC with a
                 web-based centralized management system for available
                 resources. Thanks to this proposal, researchers can run
                 scientific applications without modifying the
                 application's source code, and at the same time manage
                 thousands of computers from a single web page.
                 Summarizing, this model allows the creation of
                 on-demand customized execution environments within
                 BOINC that can be used to harness unused computational
                 resources for complex computational experiments, such
                 as EAs. To show the performance of this model, a
                 real-world application of Genetic Programming was used
                 and tested through a centrally-managed desktop grid
                 infrastructure. Results show the feasibility of the
                 approach that has allowed researchers to generate new
                 solutions by means of an easy to use and manage
                 distributed system.",
}

Genetic Programming entries for Francisco Fernandez de Vega Gustavo Olague Leonardo Trujillo Daniel Lombrana Gonzalez Rodriguez

Citations