Emergent algorithms for replica location and selection in data grid

  • Authors:
  • Víctor Méndez Muñoz;Gabriel Amorós Vicente;Félix García Carballeira;José Salt Cairols

  • Affiliations:
  • Grid and e-Science Group. Instituto de Física Corpuscular (IFIC) - mixed institute of Consejo Superior de Investigaciones Científicas (CSIC) and Universitat de València (UV) - Apt. ...;Grid and e-Science Group. Instituto de Física Corpuscular (IFIC) - mixed institute of Consejo Superior de Investigaciones Científicas (CSIC) and Universitat de València (UV) - Apt. ...;Computer Science Department. ARCOS Group. Escuela Politécnica Superior. Universidad Carlos III de Madrid. Av. Universidad 30 - 28911 Leganes, Spain;Grid and e-Science Group. Instituto de Física Corpuscular (IFIC) - mixed institute of Consejo Superior de Investigaciones Científicas (CSIC) and Universitat de València (UV) - Apt. ...

  • Venue:
  • Future Generation Computer Systems
  • Year:
  • 2010

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Abstract

Grid infrastructures for e-Science projects are growing in magnitude terms. Improvements in data Grid replication algorithms may be critical in many of these infrastructures. This paper shows a decentralized replica optimization service, providing a general Emergent Artificial Intelligence (EAI) algorithm for the problem definition. Our aim is to set up a theoretical framework for emergent heuristics in Grid environments. Further, we describe two EAI approaches, the Particle Swarm Optimization PSO-Grid Multiswarm Federation and the Ant Colony Optimization ACO-Grid Asynchronous Colonies Optimization replica optimization algorithms, with some examples. We also present extended results with best performance and scalability features for PSO-Grid Multiswarm Federation.