网格工作流调度的MOPSO方法

Yunxia Pei
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引用次数: 5

摘要

为了满足用户对网格工作流实现的QoS要求,首先对工作流的关键任务进行了分析,将整个工作流的QoS划分为多个分段,每个分段是单个任务的QoS约束。然后,提出了一种基于多目标粒子群优化(MOPSO)的网格工作流调度算法。通过正向分层和反向分层,该算法可以方便、准确地找到任务间的并行关系。该算法可以放松任务执行时间,增加调度灵活性,满足用户对QoS的要求。仿真结果表明,当NSGA-¿算法与NSGA-¿算法具有相同的截止日期时,该算法具有较短的执行时间和较低的执行成本。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A MOPSO Approach to Grid Workflow Scheduling
In order to meet user’s QoS requirement for the implementation of grid workflow, the key tasks of the workflow were analyzed firstly, and the QoS of the whole workflow was divided into segments which are the QoS-constrained of a single task. Then, a grid workflow scheduling algorithm based on multi-objective particle swarm optimization (MOPSO) was proposed. Through both positive layering and reverse layering, this algorithm can find the parallel relation between tasks easily and accurately. The algorithm can relax the task execution time, increase flexibility scheduling and meet user QoS requirements. Simulation results show that algorithm has a shorted execution time and a less execution cost compared with NSGA-¿ algorithm when the two algorithms have the same deadline.
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