期刊文献+

基于SaaS的弹性云平台优化调度策略设计 被引量:7

Elastic cloud platform optimal scheduling strategy design based on SaaS
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摘要 云计算平台利用虚拟化技术使软件应用变得更有效率的同时,也给资源管理和服务调度带来了挑战。在研究了软件服务(SaaS)与基础设施服务(IaaS)调度的区别基础上,重点考虑SaaS层的资源调度,提出基于随机理论的调度模型,把该层调度描述成一种多目标的优化问题。除了服务质量的要求,还考虑了弹性这一云服务的重要特性,并提供了任务调度与弹性服务副本的匹配策略。实验表明本调度机制的设计优化了云平台的整体性能,达到了较好的负载均衡与资源利用率。 The use of virtualization technology makes software applications more effective which deployed over cloud compu- ting platforms, but also brings challenges to the resource management and service scheduling over cloud. This paper focused on novel mechanisms which provide optimal deployment and scheduling of cloud services in SaaS scenarios on the foundation of studying some differences between IaaS and SaaS scheduling, and proposed a stochastic model to describe the scheduling process as a multi-objective optimization problem. Besides some QoS (quality of service) issues, the most significant property of cloud services-elasticity has been considered in this model, and not only the scheduling of SaaS tasks but also the arrange- ment of elastic service replicas are provided by our mechanisms. Experiment results show that the deployment and scheduling mechanisms optimize the overall performance, load halance condition as well as the resource usage of the cloud computing plat- form.
出处 《计算机应用研究》 CSCD 北大核心 2014年第2期422-425,共4页 Application Research of Computers
基金 国家教育部-中国移动研究基金资助项目(MCM20123041) 福建省教育厅科技项目(JB13198,JA13343,JA12352) 福建师范大学福清分校科技研究项目(KY2013001)
关键词 云计算 软件服务 弹性 服务副本 优化调度 cloud computing SaaS(software-as-a-service) elasticity service replica optimal scheduling
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参考文献19

  • 1BREITGAND D, EPSTEIN A. SLA-aware placement of multi-virtual machine elastic services in compute clouds [ C ]//Proc of IFIP/IEEE International Symposium on Integrated Network Management. 2011 : 161-168.
  • 2WOOD T, TARASUK-LEVIN G, SHENOY P J, et al. Memory bud- dies: exploiting page sharing for smart colocation in virtualized data centers[ C ]//Proc of ACM SIGPLAN/SIGOPS International Confe- rence on Virtual Execution Environments. New York: ACM Press, 2009 : 31 - 40.
  • 3SUDEVALAYAM S, KULKARNI P. Affinity-aware modeling of CPU usage for provisioning virtualized applications [ C ]//Proc of IEEE In- ternational Conference on Cloud Computing. 2011:139-146.
  • 4KHULLER S, LI Jian, SAHA B. Energy efficient Scheduling via par- tial shutdown[ C ]//Proc of the 21st ACM-SIAM Symosium on Dis- crete Algorithms. 2010 : 1360-1372.
  • 5LI Hui, CASALE G, ELLAHI T. SLA-driven planning and optimiza- tion of enterprise applications [ C ]//Proc of the 1st Joint WOSP/ SIPEW International Conference on Performance Engineering. New York : ACM Press, 2010 : 117-128.
  • 6ALI-ELDIN A, TORDSSON J, ELMROTH E. An adaptive hybrid elasticity controller for cloud infrastructures [ C ]//Proc of IEEE Net- work Operations and Management Symposium. 2012:204-212.
  • 7SPEITKAMP B, BICHLER M. A mathematical programming ap- proach for server consolidation problems in virtualized data centers [J]. Trans on Services Computing,2010,3(4):266-278.
  • 8BELOGLAZOV A, BUYYA R. Energy efficient allocation of virtual machines in cloud data centers [ C ]//Proc of the 10th IEEE/ACM In- ternational Conference on Cluster, Cloud and Grid Computing. 2010: 577-578.
  • 9QIN Xiao, XIE Tao. An availability-aware task scheduling strategy for heterogeneous systems [ J]. IEEE Trarls on Computers, 2008,57 (2) :188-199.
  • 10SONG S, HWANG K, KWOK Y. Risk-resilient heuristics and gene- tic algorithms for security-assured grid job scheduling [ J ]. IEEE Trans on Computers, 2006,55(6) :703-719.

二级参考文献52

  • 1孙瑞锋,赵政文.基于云计算的资源调度策略[J].航空计算技术,2010,40(3):103-105. 被引量:43
  • 2尹红军,李京,宋浒,李凌.云计算中运营商效益最优的资源分配机制[J].华中科技大学学报(自然科学版),2011,39(S1):51-55. 被引量:13
  • 3Buyya 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.
  • 4Armbrust 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.
  • 5Lin 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.
  • 6Von 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.
  • 7Ge 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.
  • 8Venkatachalam V, Franz M. Power reduction techniques for mi- croprocessor systems[J]. ACM Computing Surveys (CSUR), 2005,37(3) : 195-237.
  • 9Mezmaz 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.
  • 10Lee 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.

共引文献159

同被引文献56

  • 1郭成城,晏蒲柳.一种异构Web服务器集群动态负载均衡算法[J].计算机学报,2005,28(2):179-184. 被引量:72
  • 2Zhen Wu,Zhiyong Yu.Probabilistic interpretation for a system of quasilinear parabolic partial differential equation combined with algebra equations[J].Stochastic Processes and their Application,2014,124(12):3921-3947.
  • 3Ender Konukoglu,Ben Glocker,Darko Ziki,et al.Neighbourhood approximation using randomized forests[J].Medical Image Analysis,2013,17(7):790-804.
  • 4Jun Liu,Ting-Zhu Huang,Ivan W Selesnick,et al.Image restoration using total variation with overlapping group sparsity[J].Information Sciences,2015,295(20):232-246.
  • 5Wenguang Hou,Xuewen Wang,Mingyue Ding,et al.Adaptive image sampling through establishing 3D geometrical model[J].Expert Systems with Applications,2014,41(16):7307-7315.
  • 6Wenyu Xu,Davide Curreli,David N.Ruzic.Computational studies of thermoelectric MHD driven liquid lithium flow in metal trenches[J].Fusion Engineering and Design,2014,89(12):2868-2874.
  • 7Mishra M, Das A, Kulkarni P, et al. Dynamic resource management using virtual machine migrations[J]. Communications Magazine, IEEE, 2012, 50(9): 34-40.
  • 8Niehorster O, Brinkmann A, Fels G, et al. Enforcing SLAs in scientific clouds[C], Cluster Computing (CLUSTER), 2010 IEEE International Conference on. IEEE, 2010: 178-187.
  • 9Huang L, Chela H, Hu T. Survey on resource allocation policy and job scheduling algorithms of cloud computing[J]. Journal of Software (1796217X), 2013, 8(2): 480-487.
  • 10Binz T,, Leymann F, Schumm D. CMotion: A fi'amework for migrat/on of applications into and between clouds[C].Service-Oriented Computing and Applications (SOCA), 2011 IEEE International Conference on. IEEE, 2011: 1-4.

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