%0 Journal Article
%T Emergent algorithms for replica location and selection in data grid
%A Mendez, V.
%A Amoros, G.
%A Garcia, F.
%A Salt, J.
%J Future Generation Computer Systems
%D 2010
%V 26
%N 7
%I Elsevier Science Bv
%@ 0167-739x
%G English
%F Mendez_etal2010
%O ISI:000279804200004
%O exported from refbase (https://references.ific.uv.es/refbase/show.php?record=411), last updated on Thu, 01 Nov 2012 20:02:41 +0000
%X 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 Multiswarrn Federation.
%K Grid computing
%K Algorithms
%K Optimization methods
%K Artificial intelligence
%R 10.1016/j.future.2010.03.007
%U https://doi.org/10.1016/j.future.2010.03.007
%P 934-946