基于粒子群算法的计算网格任务调度

Hui Li, Lifeng Wang, Jianhong Liu
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引用次数: 23

摘要

传统的调度理论只能得到问题的近似最优解,而且大多是考虑单任务或独立多任务调度的算法。提出了一种解决计算网格任务调度问题的粒子群算法。建立了计算网格的任务调度模型,将粒子群算法从连续空间搜索改为整数空间搜索,选择合适的惯性权值,增强了算法的搜索能力。通过与遗传算法、混合算法和蚁群算法的比较,表明该网格任务调度算法具有一定的优势。
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Task Scheduling of Computational Grid Based on Particle Swarm Algorithm
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.
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