摘要
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.
作者
张风荣
ZHANG Feng-rong(Department of Mathematics and Information Engineering ,Liaocheng University Dongchang College, Liaocheng 252000,China)
出处
《电脑与信息技术》
2016年第6期24-26,共3页
Computer and Information Technology
基金
国家自然科学基金(项目编号:10871116)
山东省课题(项目编号:J15LN78)
聊城大学东昌学院院级课题(项目编号:2015LG001)