ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2015, Vol. 52 ›› Issue (4): 889-897.doi: 10.7544/issn1000-1239.2015.20131908

• 系统结构 • 上一篇    下一篇

基于前馈和反馈控制运行时虚拟资源动态分配

俞岭,谢奕,陈碧欢,彭鑫,赵文耘   

  1. (复旦大学计算机科学技术学院 上海 201203) (bruceyuling@163.com)
  • 出版日期: 2015-04-01
  • 基金资助: 
    基金项目:国家自然科学基金项目(61361120097);国家“八六三”高技术研究发展计划基金项目(2013AA01A605)

Towards Runtime Dynamic Provision of Virtual Resources Using Feedforward and Feedback Control

Yu Ling, Xie Yi, Chen Bihuan, Peng Xin, Zhao Wenyun   

  1. (School of Computer Science, Fudan University, Shanghai 201203)
  • Online: 2015-04-01

摘要: 随着云计算的流行和发展,越来越多的应用系统被部署在云服务器上,以可伸缩的方式按需获取虚拟资源并按使用量付费.因此,如何在保证应用系统优化运行的同时以一种考虑成本效益的方式来分配和使用虚拟资源就成了一个重要的研究问题.传统的手工调整方法不但会增加系统管理员的负担,而且准确性较差并有一定的延迟.现有的虚拟资源动态分配方法大多是在发现系统运行时质量问题后进行资源动态调整的,因此具有一定的延迟性,而且还忽略了虚拟资源的异构性带来的影响.针对这些问题,提出了一种基于控制理论的虚拟资源动态分配方法.该方法使用一个前馈控制器来动态调整虚拟资源的数量,同时使用一个反馈控制器来动态调节各个虚拟资源处理的负载比例,从而实现应用系统的优化运行和虚拟资源的有效利用.与静态虚拟资源分配方法以及仅包括前馈控制方法的对比实验表明,所提出的方法能够在保证应用系统优化运行的同时提高虚拟资源利用的有效性.

关键词: 云计算, 前馈控制, 反馈控制, 自适应, 虚拟资源, 资源分配

Abstract: With the prevalence and development of cloud computing, more and more applications are deployed on the cloud servers so as to utilize virtual resources, which can scale on-demand and are priced on a pay-per-use basis. Thus, it becomes an important research problem to ensure optimal operation of applications as well as to achieve cost-benefit provision and utilization of virtual resources. Traditional manual adjustment methods will not only increase the burden on system administrators, but also the accuracy is poor and there is a certain delay. Existing dynamic resource provision methods are mostly triggered after a runtime quality problem happens, thus involving an adaptation delay. Also, these methods neglect the negative impact of the heterogeneity of virtual resources. To address these problems, in this paper we propose a method for dynamic provision of virtual resources based on control theory. This method combines a feedforward and a feedback controller to respectively tune the number of virtual resources and the load for each virtual resource in order to achieve the optimal operation of application systems and the high-efficient use of virtual resources. An experimental study demonstrates that our method can effectively achieve optimal operation of applications as well as improve the utilization ratio of virtual resources.

Key words: cloud computing, feedforward control, feedback control, self-adaptation, virtual resources, resource provision

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