Hadoop is a perfect tool to achieve this goal with its ability to work with thousands of nodes and petabytes of data and automatically handle job scheduling, partial failure, and load balancing.

Hadoop能够处理数千个节点和pb量级的数据，可以自动地处理作业调度、部分失败和负载平衡，因此它是实现这个目标的完美工具。

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Scheduling of heterogeneous system takes aim at balancing computing load and getting minimal parallel execute time.

异构系统上调度的目标是平衡计算负载，以获得最短的并行计算时间。

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To deal with the load balancing and fault tolerance in grid computing environment, a distributed scheduling model oriented to tradition and grid service execution mechanisms was proposed.

为有效解决网格计算环境中的负载平衡和容错问题，提出了面向传统和服务执行方式的分布式调度模型。

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