首页> 外文会议>Proceedings of the 2007 International Conference on Machine Learning and Cybernetics >PRACTICAL SCHEDULING ALGORITHMS OF INDEPENDENT TASKS ON TREE-BASED GRID COMPUTING PLATFORM
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PRACTICAL SCHEDULING ALGORITHMS OF INDEPENDENT TASKS ON TREE-BASED GRID COMPUTING PLATFORM

机译:基于树的网格计算平台上独立任务的实用调度算法

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This paper discusses scheduling independent tasks on tree-based grid computing platforms, where resources have different speeds of computation and communication.Instead of minimizing the total execution time, which has been proven to be NP-hard [1], we improve integral linear planning model in [2].Using this model, the time complexity is high to obtain optimal number of tasks assigned to each computing node of multi-level tree.To address this problem, Push-Pull method is given, which transforms the linear planning of multi-lever tree into single-level tree and therefore the time complexity is greatly reduced.Based on the optimal tasks assignment to each node, a static distributed heuristic task scheduling algorithm is put forward.Experimental results show that the algorithm achives better performance than other algorithms.
机译:本文讨论了在基于树的网格计算平台上调度独立任务的方法,其中资源具有不同的计算和通信速度。我们已证明对NP困难,而不是使总执行时间最小化[1],我们改进了整体线性规划文献[2]中的模型。使用该模型,时间复杂度高,无法获得分配给多级树的每个计算节点的最佳任务数量。为了解决此问题,给出了推挽方法,该方法转换了线性规划的线性规划。将多杠杆树转换为单级树,从而大大降低了时间复杂度。基于对每个节点的最优任务分配,提出了一种静态的分布式启发式任务调度算法。实验结果表明,该算法比其他算法具有更好的性能。算法。

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