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基于接纳控制和ILP资源调度模型的BDAaaS系统架构 被引量:1

A BDAaaS System Architecture Based on Admission Control and ILP Resource Scheduling Model
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摘要 为了使云计算平台为大数据分析提供有效支持,提出一种大数据分析即服务(BDAaaS)的系统架构;首先,当用户向系统提交大数据分析应用(BDAA)时,通过接纳控制器评估任务的执行时间和成本并作出接纳决策;然后,通过服务等级协议(SLA)管理器根据任务的服务质量(QoS)需求制定SLA;最后,利用提出的整数线性规划(ILP)资源调度模型,以最小化执行成本为目标,在满足SLA下合理调度资源来执行任务;仿真结果表明,提出的方案能够有效降低任务执行时间,具有有效性和可行性。 In order to make the cloud computing platform provide effective support for large data analysis, a big data analytics as a service (BDAaaS) system architecture is proposed. First,when a user submits a big data analysis application (BDAA) to the system, the admission controller is used to evaluate the execution time and cost of the task and make an admission decision. Then, the SLA is built by the service level agreement (SLA) manager according to the Quality of Service (QoS) requirements of the tasks. Finally, the resource scheduling model based on ILP with the goal of minimize the execution cost is proposed, and used to schedule resources reasonably under satisfying the SLA. Simulation results show that the proposed scheme can effectively reduce the task execution time, which is effective and feasible.
出处 《计算机测量与控制》 2017年第3期227-230,共4页 Computer Measurement &Control
基金 公安部技术研究计划项目(2015JSYJC04) 辽宁省社科规划基金项目(L16BFX011)
关键词 云计算 大数据分析即服务 接纳控制 资源调度 整数线性规划 cloud computing big data analysis as a service admission control resource scheduling integer linear programming
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  • 1王芳,邱玉辉.一种引入轮盘赌选择算子的混合粒子群算法[J].西南师范大学学报(自然科学版),2006,31(3):93-96. 被引量:15
  • 2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
  • 3夏桂梅,曾建潮.一种基于轮盘赌选择遗传算法的随机微粒群算法[J].计算机工程与科学,2007,29(6):51-54. 被引量:27
  • 4Li Luqun.An optimistic differentiated service jobscheduling system for cloud computing service usersand providers. Proceeings of Third InternationalConference on MUE′09 . 2009
  • 5Sakellariou R,Zhao H.A hybrid heuristic for DAGscheduling on heterogeneous systems. Proceed-ings of Parallel and Distributed Processing Symposi-um . 2004
  • 6The Cloud Computing and Distributed Systems (CLOUDS)Laboratory University of Melbourne.CloudSim:a framework for modeling and simulationof cloud computing infrastructures and services. http:∥www.cloudbus.org/cloudsim/ . 2012
  • 7Buyya R,Ranjan R,Calheiros R N.Modeling andsimulation of scalable Cloud computing environ-ments and the CloudSim toolkit:Challenges and op-portunities. Proceedings of International Con-ference on High Performance Computing&Simula-tion . 2009
  • 8Tracy D Braun,Howard Jay Siegel,Noah Beck.A comparison of eleven static heuristics for mapping a class of independent tasks onto heterogeneous distributed computing systems. Journal of Parallel and Distributed Computing . 2001
  • 9K.Etminani,,M.Naghibzadeh.A Min-Min Max-Min selective algorithm for grid taskscheduling. Proeeedings of the3rd International Conferenee in Central Asiaon Internet The Next Generation of Mobile,Wireless and OPtieal CommunieationsNetworks . 2007
  • 10Rodrigo N,Calheiros,Rajiv Ret al.CloudSim:atoolkit for modeling and simulation of cloud computingenvironments and evalution of resource provisioningalgorithms. Journal of Software:Pratice andExperience . 2011

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