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A learning-based approach for fault tolerance on grid resources scheduling

机译:基于学习的网格资源调度容错方法

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While Grid environment has developed increasingly, unfortunately the importance of fault tolerance has not been remarkable in Grid resource management. On the other hand, the cost of computing by grid is important because grid is an economy-based system. Most organizations intend to spend little on their own computations by grid. Therefore, using a better approach to resource scheduling to avoid fault is necessary. This paper presents a new approach on fault tolerance mechanisms for the resource scheduling on grid by using Case-Based Reasoning technique in a local fashion. This approach applies a specific structure in order to prepare fault tolerance between exécuter nodes to retain system in a safe state with minimum data transferring. Certainly, this algorithm increases fault tolerant confidence therefore, performance of grid will be high.
机译:尽管网格环境日趋发展,但不幸的是,容错在网格资源管理中的重要性并不突出。另一方面,网格计算的成本很重要,因为网格是基于经济的系统。大多数组织打算在网格上花费很少的钱在自己的计算上。因此,有必要使用一种更好的资源调度方法来避免故障。本文提出了一种基于局部案例推理的网格资源调度中的容错机制新方法。此方法应用特定的结构,以准备执行程序节点之间的容错功能,以最少的数据传输将系统保持在安全状态。当然,该算法提高了容错置信度,因此,电网性能会很高。

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