摘要
针对如何在云计算环境下进行资源合理调度一直都是当前研究的重点。首先对云资源调度问题进行分析,然后在SFLA算法的基础上,通过在蛙群的子群划分阶段引入混沌策略,在内部搜索引入反向学习策略,在全局信息交换过程中引入动态自适应因子等方法,从而使得改进的蛙跳算法具有很好的收敛性,缩短了全局搜索和优化的时间,为复杂的云资源调度问题提供了参考模板,通过CloudSim云计算对该算法进行仿真实验。结果表明,该算法可以减少任务的平均完成时间,提高了系统处理任务的效率,在云计算资源中调度合理有效。
Aiming at how to carry out reasonable resources scheduling under the enviromment of cloud computing has always been the focus of the current research.This paper first analyzed the problem of cloud resource scheduling,and then on the basis of the basic shuffled frog leaping algorithm,through introducing the chaos strategy in the subgroup classification stage of the frog group,and bringing in the reverse learning strategy in the internal search and the dynamic adaptive factor in the process of global information exchange,made the improved shuffled frog leaping algorithm more convergent,and shortened the time of global search and optimization,provided a reference template for the complex problem of cloud resource scheduling,and performed a simulation experiment on the algorithm through CloudSim cloud computing.The results show that the improved shuffled frog leaping algorithm can reduce the average time spent in the completion of tasks,improve the efficiency of the system processing tasks and make the resource scheduling in cloud computing reasonable and effective.
出处
《计算机应用研究》
CSCD
北大核心
2014年第6期1824-1827,1832,共5页
Application Research of Computers
基金
国家自然科学基金资助项目(51276115)
关键词
蛙跳算法
服务质量
云
混沌策略
动态自适应
shuffled frog leaping algorithm（SFLA）
service quality
cloud
chaos strategy
dynamic adaptive
作者简介
李逦（1977-）,女,副教授,硕士,主要研究方向为计算机应用及网络（lnlili20132@126.com）.
姚晔（1973-）,女,教授,硕士,主要研究方向为计算机网络应用及算法设计.
李铁（1974-）,男,博导,博士,主要研究方向为计算机网络、计算机与动力工程.
