PSO vs. ACO, Data Grid Replication Services Performance Evaluation

  • Víctor Méndez
  • Felix García Carballeira
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4331)


Data Grid replication is critical for improving data intensive applications performance, providing fault tolerance and load balancing. Most of the techniques for data replication use Giggle as a framework for Replica Location Services (RLS), combined with other services for replica selection and optimization. Our previous work have proposed an enhanced Giggle framework, that simplify the location service using a flat catalogue structure, that combined with appropriate heuristic, obtain much better performances than traditional approaches. With this aim, we propose the use of Emergent Artificial Intelligence (EAI) techniques on data replication: Particle Swarm Optimisation(PSO) and Ant Colony Optimisation(ACO). This paper contribution is an experiment comparison between PSO, ACO, a canonical replication algorithm and other state of the art economic model replication algorithm. The experiments are design on two different network topologies. The simulation results confirm that PSO and ACO using the enhanced Giggle, improve performance over traditional solutions.


Market Model Data Replication Simulation Series Pheromone Concentration Grid Site 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Víctor Méndez
    • 1
  • Felix García Carballeira
    • 2
  1. 1.Universidad de Zaragoza, CPS, Edificio Ada Byron, Universidad de Zaragoza, CPSZaragozaSpain
  2. 2.Universidad Carlos III de Madrid, EPSLeganés, MadridSpain

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