基于蚁群算法的Hadoop调度算法研究

Research of Scheduling Algorithm for Hadoop Based on Ant Colony Optimization

为有效提高Hadoop集群作业调度的效率,提出一种基于蚁群算法的自适应作业调度的方案,有效利用蚁群算法正反馈的优势特点,使Hadoop作业调度器更高效地对任务进行分配,提高整体架构的作业性能。实验结果表明,该算法能够很好的平衡资源负载,减少任务的完成时间,提高系统处理任务的性能。

In order to improve the scheduling performance of Hadoop,the paper proposed a new scheduling algorithm based on ant colony optimization. By positive feedback of the ant colony,it can be more comprehensive and more scientific to assign tasks and improve the operating performance of the overall architecture.The experimental results show that this algorithm can well balanced resource load and reduce the task completion time and effectively imporove the performance of the Hadoop platform.