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云计算环境下任务调度技术的研究进展 被引量:1

Research Progresses of Task Scheduling Technology in Cloud Computing Environment
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摘要 云计算应用大规模和虚拟化的资源,通过计算机网络随时随地向用户提供基于不同需求的服务.作为影响云服务的关键因素,任务调度被认为提升云计算服务质量的有效手段之一.如何保持高效和公平,保障服务质量(QoS)和最大化用户与服务提供商的经济利益是研究的难点.论述当前云计算中任务调度算法的研究现状和发展趋势,分析符合云计算服务需求的任务调度算法的新特性.通过探讨存在的挑战和亟待解决的关键性问题,为下一步更深入的研究指出方向. Cloud computing uses very large scalable and virtualized resources to provide services based on different requirement via computer network in any time and any place. As a crucial factor affecting cloud services, task scheduling is referred to as one of the effective means of improving the quality of cloud computing services. How to keep efficiency and fairness, and how to guarantee quality of service (QOS) and maximize the economic interests of the users and service providers are difficult problems for study. Though an in-depth study of the major research works on this field, this paper reviews the research status and development trend of task scheduling algorithms in cloud computing environment, and analyzes new features of task scheduling technology to meet the needs of cloud computing service. Finally, by discussing existing challenges and key problems that needs to be solved, the next research orientation will be found.
出处 《玉林师范学院学报》 2014年第2期2-9,共8页 Journal of Yulin Normal University
基金 国家自然科学基金资助项目(61363067 60963022)
关键词 云计算 任务调度 虚拟机器 服务质量(QoS) cloud computing task scheduling virtual machines QOS
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参考文献26

  • 1M. Armbrust, A. Fox, R. Griffith et al. Above the Clouds: A Berkeley View of Cloud Computing[R]. University of California, Berkeley: Technical Report(UCB/ EECS-2009-28), February 10, 2009.
  • 2张希翔.云计算环境下任务调度算法的研究[D].硕士学位论文,南宁:广西大学,2011.
  • 3S. Nagadevi, K.Satyapriya and D.Malathy. A Survey on Economic Cloud Schedulers for Optimized Task Scheduling[J].Intemational Journal of Advanced Engineering Technology, 2013, 4(1):58-62.
  • 4W. Yao, B. Li and J. You.Genetic Scheduling on Minimal Processing Elements in the Grid[M]. Lecture Notes in Computer Sciences 2557, Springer-Verlag Berlin, Berlin, 2002. pp.465-476.
  • 5遆鸣,陈俊杰,强彦.基于模拟退火的Map Reduce调度算法[J].计算机工程,2012,38(19):45-48. 被引量:9
  • 6X. He, X. Sun and G..Laszewski. A QoS Guided Min-Min Heuristic for Grid Task Scheduling [J]. Journal of Computer Science and Technology, 2003, 18(4): 442-451.
  • 7王登科,李忠.基于粒子群优化与蚁群优化的云计算任务调度算法[J].计算机应用与软件,2013,30(1):290-293. 被引量:43
  • 8M. Abdeyazdan, S. Parsa and A. M. Rahmani. Task Graph Pre-scheduling, Using Nash Equilibrium in Game Theory [J].The Journal of Supercomputing, 2013, 64 (1):177-203.
  • 9张希翔,李陶深.云计算下适应用户任务动态变更的调度算法[J].华中科技大学学报(自然科学版),2012,40(S1):165-169. 被引量:5
  • 10M. A. Arleen, K. Pawlikowski and A. Willig. A Framework for Resource Allocation Strategies in Cloud Computing Environment[C]. Proceeding of 2011 IEEE 35th Annual Computer Software and Applications Conference Workshops , Munich , Germany, July 18-22, 2011, pp.261-266.

二级参考文献41

  • 1杜晓丽,蒋昌俊,徐国荣,丁志军.一种基于模糊聚类的网格DAG任务图调度算法[J].软件学报,2006,17(11):2277-2288. 被引量:48
  • 2米勒.云计算[M].史美林,姜进磊,孙瑞志,等译.北京:机械工业出版社,2009:125-128.
  • 3FOSTER I, YONG ZHAO, RAICU I, et al. Cloud computing and grid computing 360-degree compared[C] // Proceedings of the 2008 Grid Computing Environments Workshop. Washington, DC: IEEE Computer Society, 2008:1 - 10.
  • 4ARMBRUST M, FOX A, GRIFFITH R, et al. Above the clouds: A Berkeley view of cloud eomputing[EB/OL]. [2010 -01 -25]. http://www, eecs. berkeley, edu/Pubs/TechRpts/20Og/EECS-20og- 28. pdf.
  • 5BARROSO L A, DEAN J, HOLZLE U. Web search for a planet: the google cluster architecture[J]. IEEE Micro, 2003, 23(2) : 22 - 28.
  • 6CHIEN A, CALDER B, ELBERT S, et al. Entropia: Architecture and performance of an enterprise desktop grid system[J]. Journal of Parallel and Distributed Computing, 2003, 63(5):597-610.
  • 7KIM J S, NAM B, MARSH M, et al. Creating a robust desktop grid using peer-to-peer services[EB/OL]. [ 2009 - 10 - 16]. ftp://ftp. cs. umd. edu/pub/hpsl/papers/papers-pdf/ngs07.pdf.
  • 8ABRAHAM A, BUYYA R, NATH B. Nature's heuristics for scheduling jobs on computational grids[ C]// The 8th International Conference on Advanced Computing and Communications. New Delhi: Tata McGraw-Hill Publishing, 2000:45-52.
  • 9DEAN J, GHEMAWAT S. MapReduce: simplified data processing on large clusters[ C]//Proceedings of the 6th Symposium on Operating System Design and Implementation. New York: ACM, 2004:137 - 150.
  • 10The CLOUDS Lab. Gridsim[ EB/OL]. [ 2010 - 06 - 25]. http:// www. cloudbus. org/gridsim/.

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