自适应邻域的多目标网格任务调度算法

《自适应邻域的多目标网格任务调度算法》由会员上传分享，免费在线阅读，更多相关内容在教育资源-天天文库。

1、自适应邻域的多目标网格任务调度算法摘要:针对网格计算中的多目标网格任务调度问题,提出了一种基于自适应邻域的多目标网格任务调度算法。该算法通过求解多个网格任务调度目标函数的非劣解集,采用自适应邻域的方法来保持网格任务调度多目标解集的分布性,尝试解决网格任务调度中多目标协同优化问题。实验结果证明,该算法能够有效地平衡时间维度和费用维度目标,提高了资源的利用率和任务的执行效率,与min-min和max-min算法相比具有较好的性能。关键词:网格任务调度算法;多目标进化算法;自适应邻域;任务调度multi-objectiveevolutionaryalgorithmforgridjobs

2、chedulingbasedonadaptiveneighborhood英文作者名yangming1,2*,xuesheng-jun2,chenliang1,liuyong-sheng1英文地址(1.zhejiangmeteorologicalinformationnetworkcenter,hangzhouzhejiang310017,china;2.collegeofcomputerandsoftware,nanjinguniversityofinformationscienceandtechnology,nanjingjiangsu210044,china)abstract

3、:anewadaptiveneighborhoodmulti-objectivegridtaskschedulingalgorithm(anmo-gtsa)wasproposedinthis自适应邻域的多目标网格任务调度算法摘要:针对网格计算中的多目标网格任务调度问题,提出了一种基于自适应邻域的多目标网格任务调度算法。该算法通过求解多个网格任务调度目标函数的非劣解集,采用自适应邻域的方法来保持网格任务调度多目标解集的分布性,尝试解决网格任务调度中多目标协同优化问题。实验结果证明,该算法能够有效地平衡时间维度和费用维度目标,提高了资源的利用率和任务的执行效率,与min-min和ma

4、x-min算法相比具有较好的性能。关键词:网格任务调度算法;多目标进化算法;自适应邻域;任务调度multi-objectiveevolutionaryalgorithmforgridjobschedulingbasedonadaptiveneighborhood英文作者名yangming1,2*,xuesheng-jun2,chenliang1,liuyong-sheng1英文地址(1.zhejiangmeteorologicalinformationnetworkcenter,hangzhouzhejiang310017,china;2.collegeofcomputerand

5、software,nanjinguniversityofinformationscienceandtechnology,nanjingjiangsu210044,china)abstract:anewadaptiveneighborhoodmulti-objectivegridtaskschedulingalgorithm(anmo-gtsa)wasproposedinthispaperforthemulti-objectivejobschedulingcollaborativeoptimizationproblemingridcomputing.intheanmo-gtsa,a

6、nadaptiveneighborhoodmethodwasappliedtofindthenon-inferiorsetofsolutionsandmaintainthediversityofthemulti-objectivejobschedulingpopulation.theexperimentalresultsindicatethatthealgorithmproposedinthispapercannotonlybalancethemulti-objectivejobscheduling,butalsoimprovetheresourceutilizationande

7、fficiencyoftaskexecution.moreover,theproposedalgorithmcanachievebetterperformanceontime-dimensionandcost-dimensionthanthetraditionalmin-minandmax-minalgorithms.keywords:gridjobschedulingalgorithm;multi-objectiveevolutionaryalgorithm;adaptiven