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As a new computing pattern, Grid computing makes the aggregation, selection, and sharing of geographically distributed heterogeneous resources possible to solve large-scale issues of commerce, engineering, and science. However, it is problematic that the geographic distributed resources owned by different institutions with their different price models, usage policies and changing load. The resource...
Optimizing job scheduling is the major issue in achieving high performance in grid computing systems. The grid workload consists of multiple jobs and the execution precedence constraints can be represented by a Directed Acyclic Graph. Genetic algorithms are useful to resolve large scale combinatorial prediction and optimization problems. In this paper, we represent a Coarse-grained parallel genetic...
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