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虚拟化技术在云计算数据中心中的应用研究 被引量:3

The Research on Cloud Computing Datacenter Based Virtualization
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摘要 通过对云计算数据中心提高资源利用率和用户QOS的需求进行分析,围绕其中的关键技术虚拟化技术,从服务器虚拟化、网络虚拟化、存储虚拟化三个方面进行总结,针对云计算平台建立其可用性模型,分析了IAAS,PAAS,SAAS三种云服务模式的可用性计算方法,最后通过实验验证了云计算可用性参考模型适用于常见的云服务模式。 Through the demand for cloud computing data center to improve resource utilization, three aspects were summarized, server virtualization, network virtualization and storage virtualization. Availability model is established for the cloud computing platform, and the IAAS, PAAS, SAAS three cloud service model were analyzed. At Result, experiments validated that the avail-ability of cloud computing model was suitable for the common cloud service model.
作者 王小军 朱祎 WANG Xiao-jun, ZHU Yi (Network Center, Jiangsu Open University, Nanjing 210036, China)
出处 《电脑知识与技术》 2014年第2期677-679,共3页 Computer Knowledge and Technology
基金 江苏开放大学“十二五”规划课题(12SEW-Q-071),(13SEW-Q-052),(12SEW-Z-009)
关键词 虚拟化 云计算 数据中心 可用性 virtualization cloud computing sata center availability
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  • 1Buyya R, Yeo C S, Venugopal S, et al. Cloud computing and e-merging IT platforms: vision, hype, and reality for delivering computing as the 5th utility[J]. Future Generation Computer Systems,2009,25(6) :599-616.
  • 2Armbrust M, Fox A, Griffith R, et al. Above the Clouds: A Berkeley View of Cloud Computing [EB/OL]. http..//www, ee- cs. berkeley, edu/Pubs/TechRpts/2009/EECS-2009-28, html, February 2009.
  • 3Lin Wei-wei, Qi De-yu. Research on Resource Self-Organizing Model for Cloud Computing[C]// 2010 International Conference on Internet Technology and Applications. 2010:1-5.
  • 4Von L G, Wang L, Younge A J, et al. Power-Aware Scheduling of Virtual Machines in DVFS-enabled Clusters[C] ff Proc. of IEEE International Conference on Cluster Computing 2009. New Orleans, LA, USA, 2009 : 1-10.
  • 5Ge R, Feng X, Cameron K. Performance-constrained distributed dvs scheduling for scientific applications on power-aware clus ters[C]//Proceedings of the 2005 ACM/IEEE Conference on Supercomputing. IEEE Computer Society, Washington DC, USA, 2005 : 34.
  • 6Venkatachalam V, Franz M. Power reduction techniques for mi- croprocessor systems[J]. ACM Computing Surveys (CSUR), 2005,37(3) : 195-237.
  • 7Mezmaz M, MelabN, KessaciY, etal. Aparallel bi-objective hy- brid metaheuristic for energy-aware scheduling for cloud compu- ting systems[J]. Journal of Parallel and Distributed Computing (JPDC), 2011,71(11) : 1497-1508.
  • 8Lee Y C,Zomaya A Y. A novel state transitionmethod formeta- heuristic-based scheduling in heterogeneous computing systems [J]. IEEE Transactions on Parallel and Distributed Systems, 2008,19(9) : 1215-1223.
  • 9Beloglazov A, Abawajy J, Buyya R. Energy-Aware Resource Al- location Heuristics for Efficient Management of Data Centers for Cloud Computing[J]. Future Generation Computer Systems, 2012,28(5) : 755-768.
  • 10Buyya R, Beloglazov A, Abawajy J. Energy-Efficient Manage- ment of Data Center Resources for Cloud Computing:A Vision, Architectural Elements,and Open Challenges[C]//Proceedings of the 2010 International Conference on Parallel and Distributed Processing Techniques and Applications ( PDPTA2010 ). Las Vegas, USA, July 2010.

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