Enhanced resource scheduling in Grid considering overload of different attributes

Enhanced resource scheduling in Grid considering overload of different attributes
复制标题

考虑不同属性过载的网格中增强的资源调度

DOI:
10.3837/tiis.2016.03.007
复制
发表时间:
2016-03
影响因子:
1.5
通讯作者:
Hao YS
Hao YS
中科院分区:
计算机科学4区
文献类型:
--
作者:
Hao Yongsheng;Hao Yongsheng;Hao YS;Hao YS

文献摘要

参考文献

被引文献

相似文献

网格中的调度方法大多只考虑资源的一个特殊属性或作业的一个服务质量(Quality of Service,QOS)。在本文中,我们重点研究如何同时考虑这两方面的问题。根据作业的需求和资源的属性,将作业分为三类:CPU过载作业、内存过载作业和带宽过载作业。根据不同的属性,一个作业可能属于不同的类别。对不同类别的作业按不同的顺序进行调度,提出了一种网格资源调度方法--多属性调度方法MTS。通过与Min-min、ASJS和MRS(多维调度)方法的比较,结果表明:(1)MTS比其他方法减少了15%以上的执行时间;(2)MTS提高了在作业截止日期前完成的作业数量;(3)MTS增加了传输文件(输入文件和输出文件)的文件大小,并增加了完成作业的指令数量。
Most of scheduling methods in the Grid only consider one special attribute of the resource or one aspect of QoS (Quality of Service) of the job. In this paper, we focus on the problem that how to consider two aspects simultaneously. Based on the requirements of the jobs and the attributes of the resources, jobs are categorized into three kinds: CPU-overload, memory-overload, and bandwidth-overload jobs. One job may belong to different kinds according to different attributes. We schedule the jobs in different categories in different orders, and then propose a scheduling method-MTS (multiple attributes scheduling method) to schedule Grid resources. Based on the comparisons between our method, Min-min, ASJS (Adaptive Scoring Job Scheduling), and MRS (Multi-dimensional Scheduling) show: (1) MTS reduces the execution time more than 15% to other methods, (2) MTS improves the number of the finished jobs before the deadlines of the jobs, and (3) MTS enhances the file size of transmitted files (input files and output files) and improves the number of the instructions of the finished jobs.
DOI: 10.1109/pesgm.2016.7741095
发表时间: 2016-07
期刊: 2016 IEEE Power and Energy Society General Meeting (PESGM)
影响因子: --
作者:
T. Hansen;Robin Roche;Siddharth Suryanarayanan;A. A. Maciejewski-A.;H. Siegel
通讯作者: T. Hansen;Robin Roche;Siddharth Suryanarayanan;A. A. Maciejewski-A.;H. Siegel
DOI: 10.1016/j.future.2011.06.013
发表时间: 2012-07
期刊: Future Gener. Comput. Syst.
影响因子: --
作者:
Reda Albodour;Anne E. James;Norlaily Yaacob
通讯作者: Reda Albodour;Anne E. James;Norlaily Yaacob
DOI: 10.1016/j.future.2011.09.002
发表时间: 2012-03
期刊: Future Gener. Comput. Syst.
影响因子: --
作者:
Valliyammai Chinnaiah;T. Somasundaram
通讯作者: Valliyammai Chinnaiah;T. Somasundaram
DOI: 10.1007/s10723-009-9132-5
发表时间: 2009-08
影响因子: 5.5
作者:
T. Rings;G. Caryer;Julian Robert Gallop;J. Grabowski;T. Kováčiková;S. Schulz;I. Stokes-Rees
通讯作者: T. Rings;G. Caryer;Julian Robert Gallop;J. Grabowski;T. Kováčiková;S. Schulz;I. Stokes-Rees
DOI: 10.1007/s11227-010-0539-3
发表时间: 2012-03
期刊: The Journal of Supercomputing
影响因子: --
作者:
Kalim Qureshi;Babar Majeed;J. Kazmi;S. Madani
通讯作者: Kalim Qureshi;Babar Majeed;J. Kazmi;S. Madani