基于渐进式蚁群优化的多处理器任务分配（英文）

发布时间：2018-05-31 06:29

本文选题：蚁群优化 + 列表调度　；参考：《Frontiers of Information Technology & Electronic Engineering》2017年04期

【摘要】：任务调度优化是多处理器环境(如并行和分布式系统)取得良好性能所面临的最重要挑战之一。目前大多数任务调度算法基于列表调度法,该方法的基本思路是,以列表的形式准备一系列待调度的节点,赋予这些节点不同优先级,然后不断去除列表中优先级最高的节点,并将其分配给具有最早开始时间(Earliest start time,EST)的处理器。由此可见,该算法的完成时间主要由两大因素决定:(1)任务分配顺序的选择(次序子问题);(2)选定顺序的任务如何分配给处理器(分配子问题)。已有文献提出了许多解决次序子问题的好办法,但分配子问题少有人涉及。本文研究结果显示:传统的按照最早开始时间分配任务的方法并非最优;基于蚁群优化算法,得到一种新的方法,可以获得高效得多的调度方案。
[Abstract]:Task scheduling optimization is one of the most important challenges for multiprocessor environments (such as parallel and distributed systems) to achieve good performance. At present, most task scheduling algorithms are based on list scheduling method. The basic idea of this method is to prepare a series of nodes to be scheduled in the form of lists, give these nodes different priorities, and then constantly remove the highest priority nodes in the list. And assign it to processors with the earliest start time, Earliest start EST. It can be seen that the completion time of the algorithm is mainly determined by two major factors: 1) how to assign the tasks in the selected order to the processor (assignment subproblem). Many good methods have been put forward to solve the order sub-problem, but the allocation sub-problem is seldom involved. The results show that the traditional method of assigning tasks according to the earliest start time is not optimal. Based on ant colony optimization algorithm, a new method can be obtained to obtain a much more efficient scheduling scheme.
【作者单位】： Sama
【基金】：Project supported by Sama Technical and Vocational Training College,Islamic Azad University,Shoushtar Branch,Shoushtar,Iran
【分类号】：TP18;TP332

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