计算集群环境下的动态任务调度

骈文研究 Pub Date : 2004-07-05 DOI:10.1109/ISPDC.2004.21
I. Savvas, Mohand Tahar Kechadi
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引用次数: 20

摘要

本研究采用集群计算环境作为计算平台。为了提高系统的效率,提出了一种动态任务调度算法,在集群节点间均衡负载。该技术是动态的、非先发制人的、自适应的,并且使用混合的集中和分散策略。该算法基于分而治之的原则,将集群建模为超网格,然后在超网格之间平衡负载。递归地,维度k的超网格被划分为维度k - 1的网格,直到维度为1。然后,集群中所有节点的负载几乎相等。为了获得最佳性能,选择了超电网的最优尺寸。仿真结果表明了该算法的有效性。此外,我们确定了算法可以被触发的临界点(下界)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Dynamic task scheduling in computing cluster environments
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.
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