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Task Scheduling of Computational Grid Based on Particle Swarm Algorithm

机译:基于粒子群算法的计算网格任务调度

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The traditional scheduling theory can only get the approximate optimal solution of the problem, and most is to consider algorithms on a single task or independent multitask scheduling. It presents a particle swarm algorithm to solve the task scheduling problem of computational grid. It builds a task scheduling model of computational grid, changes the particle swarm algorithm in continuous space searching to an integer space searching, selects the appropriate inertia weight value, and enhances the searching capabilities of the algorithm. Through comparison with genetic algorithm, hybrid algorithm, and ant algorithm, the results show that the grid task scheduling algorithm has some advantages.
机译:传统的调度理论只能获得问题的近似最优解,而大多数是在单任务或独立的多任务调度中考虑算法。提出了一种粒子群算法来解决计算网格的任务调度问题。建立了计算网格的任务调度模型,将连续空间搜索中的粒子群算法改变为整数空间搜索,选择合适的惯性权重值,增强了算法的搜索能力。通过与遗传算法,混合算法和蚂蚁算法的比较,结果表明网格任务调度算法具有一定的优势。

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