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Dynamic task scheduling in computing cluster environments

机译:计算群集环境中的动态任务调度

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In this study, a cluster-computing environment is employed as a computational platform. In order to increase the efficiency of the system, a dynamic task scheduling algorithm is proposed, which balances the load among the nodes of the cluster. The technique is dynamic, nonpreemptive, adaptive, and it uses a mixed centralised and decentralised policies. Based on the divide and conquer principle, the algorithm models the cluster as hyper-grids and then balances the load among them. Recursively, the hyper-grids of dimension k are divided into grids of dimensions k - 1, until the dimension is 1. Then, all the nodes of the cluster are almost equally loaded. The optimum dimension of the hyper-grid is chosen in order to achieve the best performance. The simulation results show the effective use of the algorithm. In addition, we determined the critical points (lower bounds) in which the algorithm can to be triggered.
机译:在本研究中,群集计算环境被用作计算平台。为了提高系统的效率,提出了一种动态任务调度算法,其平衡了集群的节点之间的负载。该技术是动态的,非掠夺性的,自适应,它使用混合的集中和分散的政策。基于划分和征服原理,算法将群集绘制为超网格,然后平衡它们之间的负载。递归地,尺寸k的超网格被分成尺寸K - 1的网格,直到尺寸为1.然后,群集的所有节点都几乎同等地加载。选择超网格的最佳维度,以实现最佳性能。仿真结果显示了算法的有效利用。此外,我们确定了算法可以触发算法的关键点(下限)。

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