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EvoSpace: A Distributed Evolutionary Platform Based on the Tuple Space Model

  • Mario García-Valdez
  • Leonardo Trujillo
  • Francisco Fernández de Vega
  • Juan J. Merelo Guervós
  • Gustavo Olague
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7835)

Abstract

This paper presents EvoSpace, a Cloud service for the development of distributed evolutionary algorithms. EvoSpace is based on the tuple space model, an associatively addressed memory space shared by several processes. Remote clients, called EvoWorkers, connect to EvoSpace and periodically take a subset of individuals from the global population, perform evolutionary operations on them, and return a set of new individuals. Several EvoWorkers carry out the evolutionary search in parallel and asynchronously, interacting with each other through the central repository. EvoSpace is designed to be domain independent and flexible, in the sense that in can be used with different types of evolutionary algorithms and applications. In this paper, a genetic algorithm is tested on the EvoSpace platform using a well-known benchmark problem, achieving promising results compared to a standard evolutionary system.

Keywords

Distributed Evolutionary Algorithms Tuple Space Cloud Computing 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Mario García-Valdez
    • 1
  • Leonardo Trujillo
    • 1
  • Francisco Fernández de Vega
    • 2
  • Juan J. Merelo Guervós
    • 3
  • Gustavo Olague
    • 4
  1. 1.Instituto Tecnológico de TijuanaTijuanaMexico
  2. 2.Grupo de Evolución ArtificialUniversidad de ExtremaduraMéridaSpain
  3. 3.Universidad de GranadaGranadaSpain
  4. 4.Centro de Investigación Científica y de Educación Superior de EnsenadaEnsenadaMexico

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