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Scheduling on the Grid : Historical Trace and Dynamic Heuristics

Identifieur interne : 001220 ( Crin/Checkpoint ); précédent : 001219; suivant : 001221

Scheduling on the Grid : Historical Trace and Dynamic Heuristics

Auteurs : Yves Caniou ; Emmanuel Jeannot

Source :

RBID : CRIN:caniou02b

English descriptors

Abstract

We present a historical trace manager and new dynamic scheduling heuristics that can be used, and are studied, in the client-agent-server model on the `grid'. These heuristics rely on the common acknowledgment of the characteristics of the tasks submitted to the agent, but also on the construction of the underlying historical trace of the different tasks submitted to each server. We study each heuristic and compare them on several metrics to an instantiation of MCT (Minimum Completion time), chosen as reference heuristic. The simulation experiments we have conducted show that they are likely to give good results when tested in a real environment.

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CRIN:caniou02b

Le document en format XML

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<div type="abstract" xml:lang="en" wicri:score="1767">We present a historical trace manager and new dynamic scheduling heuristics that can be used, and are studied, in the client-agent-server model on the `grid'. These heuristics rely on the common acknowledgment of the characteristics of the tasks submitted to the agent, but also on the construction of the underlying historical trace of the different tasks submitted to each server. We study each heuristic and compare them on several metrics to an instantiation of MCT (Minimum Completion time), chosen as reference heuristic. The simulation experiments we have conducted show that they are likely to give good results when tested in a real environment.</div>
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<abstract>We present a historical trace manager and new dynamic scheduling heuristics that can be used, and are studied, in the client-agent-server model on the `grid'. These heuristics rely on the common acknowledgment of the characteristics of the tasks submitted to the agent, but also on the construction of the underlying historical trace of the different tasks submitted to each server. We study each heuristic and compare them on several metrics to an instantiation of MCT (Minimum Completion time), chosen as reference heuristic. The simulation experiments we have conducted show that they are likely to give good results when tested in a real environment.</abstract>
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