PSO vs. ACO, Data Grid Replication Services Performance Evaluation
نویسندگان
چکیده
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.
منابع مشابه
PSO-Grid Data Replication Service
Data grid replication is critical for improving the performance of data intensive applications. Most of the used techniques for data replication use Replica Location Services (RLS) to resolve the logical name of files to its physical locations. An example of such service is Giggle, which can be found in the OGSA/Globus architecture. Classical algorithms also need some catalog and optimization s...
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