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ECJ+HADOOP: An Easy Way to Deploy Massive Runs of Evolutionary Algorithms

  • Francisco ChávezEmail author
  • Francisco Fernández
  • César Benavides
  • Daniel Lanza
  • Juan Villegas
  • Leonardo Trujillo
  • Gustavo Olague
  • Graciela Román
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9598)

Abstract

This paper describes initial steps towards allowing Evolutionary Algorithms (EAs) researchers to easily deploy computing intensive runs of EAs on Big Data infrastructures. Although many proposals have already been described in the literature, and a number of new software tools have been implemented embodying parallel versions of EAs, we present here a different approach. Given traditional resistance to change when adopting new software, we try instead to endow the well known ECJ tool with the MapReduce model. By using the Hadoop framework, we introduce changes in ECJ that allow researchers to launch any EA problem on a big data infrastructure similarly as when a single computer is used to run the algorithm. By means of a new parameter, researchers can choose where the run will be launched, whether in a Hadoop based infrastructure or in a desktop computer. This paper shows the tests performed, how the whole system has been tuned to optimize the running time for ECJ experiments, and finally a realworld problem is shown to describe how the MapReduce model can automatically deploy the tasks generated by ECJ without additional intervention.

Keywords

Multi-objective evolutionary algorithm Face recognition Hadoop ECJ 

Notes

Acknowledgements

This work has been supported by FP7-PEOPLE-2013-IRSES, Grant 612689 ACoBSEC, Spanish Ministry of Economy, Project UEX:EPHEMEC (TIN2014-56494-C4-2-P); Junta de Extremadura, and FEDER, project GR15068. Also it has been supported by CONACyT México by the project 155045 – “Evolución de Cerebros Artificiales en Visión por Computadora” and TESE by the project DIMI-MCIM-004/08.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Francisco Chávez
    • 1
    Email author
  • Francisco Fernández
    • 1
  • César Benavides
    • 2
  • Daniel Lanza
    • 3
  • Juan Villegas
    • 4
  • Leonardo Trujillo
    • 5
  • Gustavo Olague
    • 6
  • Graciela Román
    • 2
  1. 1.Department of Computer ScienceUniversity of ExtremaduraMéridaSpain
  2. 2.Departamento de Ing. EléctricaUniversidad Autónoma Metropolitana, IztapalapaMexico, D.F.Mexico
  3. 3.CERN, European Organization for Nuclear ResearchMeyrinSwitzerland
  4. 4.Departamento de ElectrónicaUniversidad Autónoma Metropolitana, AzcapotzalcoMexico, D.F.Mexico
  5. 5.Instituto Tecnológico de TijuanaTijuanaMexico
  6. 6.CICESEEnsenadaMexico

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