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Grid computing is a mainstream technology to integrate large scale distributed sharing resources. To achieve the promising potentials of tremendous distributed resources, effective and efficient scheduling algorithms are fundamentally important. Most of the applications in grid computing fall into interdependent task model called workflow application. Task scheduling is a fundamental issue in achieving high performance in grid computing systems. It is well known that the complexity of a general scheduling problem is NP-Complete. The grid workflow task scheduling problem is described by a Directed Acyclic Graph (DAG) or task graph. The graph represents the dependency among tasks, their computation time and communication time between them.
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