[1]黄 纬,温志萍,程 初.云计算中基于K-均值聚类的虚拟机调度算法研究[J].南京理工大学学报(自然科学版),2013,37(06):807-812.
 Huang Wei,Wen Zhiping,Cheng Chu.Virtual machine scheduling algorithm based on K-means clustering in cloud computing[J].Journal of Nanjing University of Science and Technology,2013,37(06):807-812.
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云计算中基于K-均值聚类的虚拟机调度算法研究
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《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

卷:
37卷
期数:
2013年06期
页码:
807-812
栏目:
出版日期:
2013-12-31

文章信息/Info

Title:
Virtual machine scheduling algorithm based on K-means clustering in cloud computing
作者:
黄 纬温志萍程 初
南京工程学院 计算机工程学院,江苏 南京 211167
Author(s):
Huang WeiWen ZhipingCheng Chu
School of Computer Engineering,Nanjing Institute of Technology,Nanjing 211167,China
关键词:
云计算 K-均值聚类 虚拟机 调度 贪婪算法
Keywords:
cloud computing K-means clustering virtual machine scheduling greedy algorithm
分类号:
TP311
摘要:
为了提高云计算数据中心的资源利用率,动态优化部署虚拟机,提出基于K-均值聚类的虚拟机调度算法。使用虚拟机资源配置的相关性作为聚类的衡量标准,将虚拟机放置于与其资源互补的物理节点上,从而充分利用其资源,并具有高效稳定的特点。进一步设计了在线调度算法处理新到达虚拟机的请求。提出了贪婪算法,并给出了其与最优离线算法竞争比的上界。基于真实数据集的实验结果证实了算法的正确性。
Abstract:
To improve the resource utilization of cloud computing data centers and optimize virtual machines dynamically,a virtual machine scheduling algorithm is proposed based on K-means clustering.The correlation of virtual machine resource allocation is used as the standard of clustering,and a virtual machine is placed on the physical node complementary to it on resource,so that its resource is used fully and it is effective and stable.An online scheduling algorithm is designed to handle the requirements of new virtual machines.A greedy algorithm is proposed,and the upper bound of the competitive ratio between it and the optimal offline algorithm is given.The correctness of this algorithm is verified based on the experimental results of real data sets.

参考文献/References:

[1] 陈康,郑纬民.云计算:系统实例与研究现状[J].软件学报,2009,20(5):1337-1348.
Chen Kang,Zheng Weimin.Cloud computing:System instances and current research[J].Journal of Software,2009,20(5):1337-1348.
[2]宋杰,李甜甜,闫振兴,等.一种云计算环境下的能效模型和度量方法[J].软件学报,2012,23(2):200-214.
Song Jie,Li Tiantian,Yan Zhenxing,et al.Energy-efficiency model and measuring approach for cloud computing[J].Journal of Software,2012,23(2):200-214.
[3]Barham P,Dragovic B,Fraser K et al.Xen and the art of virtualization[A].Proceedings of the 19th ACM Symposium on Operating Systems Principles[C].New York,USA:ACM,2003:164-177.
[4]Nurmi D,Wolski R,Grzegorczyk C et al.The Eucalyptus open-source cloud-computing system[A].Cluster Computing and the Grid[C].Shanghai:IEEE,2009:124-131.
[5]Zhu Q,Zhu J,Agrawal G.Power-aware consolidation of scientific workflows in virtualized environments[A].Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing,Networking,Storage and Analysis[C].Washington DC,USA:IEEE,2010:1-12.
[6]Meng X,Isci C,Kephart J,et al.Efficient resource provisioning in compute clouds via VM multiplexing[A].Proceedings of the 7th International Conference on Autonomic Computing[C].NewYork,USA:ACM,2010:11-20.
[7]Bobroff N,Kochut A,Beaty K.Dynamic placement of virtual machines for managing SLA violations[A].10th IFIP/IEEE International Symposium on Intergrated Network Management[C].Munich,Germany:IEEE,2007:119-128.
[8]Minghong L,Wierman A,Andrew L L H et al.Dynamic right-sizing for power-proportional data centers[A].INFOCOM[C].Shanghai:IEEE,2011:1098-1106.
[9]Bin packing problem[EB/OL].http://en.wikipedia.org/wiki/Bin_packing_problem,2013-12-16.
[10]Epstein L,Stee R.Optimal online bounded space multidimensional packing[A].SODA[C].Philadelphia,USA:ACM,2004:214-223.
[11]Sonnek J,Chandra A.Virtual putty:Reshaping the physical footprint of virtual machines[A].Proceedings of the 2009 Conference on Hot Topics in Cloud Computing[C].San Diego,USA:ACM,2009.
[12]Seiden S S.On the online bin packing problem[J].Journal of the ACM,2002,49(5):640-671.
[13]Wood T,Shenoy P,Venkataramani A,et al.Black-box and gray-box strategies for virtual machine migration[A].Proceedings of the 4th USENIX Symposium on Networked Systems Design and Implementation[C].Berkeley,USA:USENIX Association,2007:229-242.
[14]Jayasinghe D,Pu C,Eilam T,et al.Improving perfor-mance and availability of services hosted on IaaS clouds with structural constraint-aware virtual machine placement[A].Services Computing[C].Washington DC,USA:IEEE,2011:72-79.
[15]Khanna G,Beaty K,Kar G,et al.Application perfor-mance management in virtualized server environments[A].Network Operations and Mangement Symposium[C].Vancouver,Canada:IEEE,2006:373-381.
[16]Meng X,Pappas V,Zhang L.Improving the scalability of data center networks with traffic-aware virtual machine placement[A].INFOCOM[C].San Diego,USA:IEEE,2010:1-9.
[17]Hermenier F,Lorca X,Menaud J M,et al.Entropy:a consolidation manager for clusters[A].Proceedings of the 2009 ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environment[C].New York,USA:IEEE,2009:41-50.

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备注/Memo

备注/Memo:
收稿日期:2013-01-22 修回日期:2013-10-25
基金项目:南京工程学院校级科研基金(创新基金)(CKJ2010010)
作者简介:黄纬(1973-),女,博士,副教授,主要研究方向:分布式计算、软件工程等,E-mail:wweihuang@sina.com。
引文格式:黄纬,温志萍,程初.云计算中基于K-均值聚类的虚拟机调度算法研究[J].南京理工大学学报,2013,37(6):807-812.
投稿网址:http://njlgdxxb.paperonce.org
更新日期/Last Update: 2013-12-31