计算机科学 ›› 2017, Vol. 44 ›› Issue (10): 19-25.doi: 10.11896/j.issn.1002-137X.2017.10.004

• • 上一篇    下一篇

数据中心虚拟机节能管理机制

朱德剑,白光伟,蔡炎伟,任栋,沈航   

  1. 南京工业大学计算机科学与技术系 南京210009,南京工业大学计算机科学与技术系 南京210009,南京工业大学计算机科学与技术系 南京210009,南京工业大学计算机科学与技术系 南京210009,南京工业大学计算机科学与技术系 南京210009
  • 出版日期:2018-12-01 发布日期:2018-12-01
  • 基金资助:
    本文受国家自然科学基金项目(61502230,7),江苏省自然科学基金项目(BK20150960),江苏省普通高校自然科学研究项目(15KJB520015),江苏省六大高峰人才基金资助

Energy-aware Management of Virtual Machines in Data Center

ZHU De-jian, BAI Guang-wei, CAI Yan-wei, REN Dong and SHEN Hang   

  • Online:2018-12-01 Published:2018-12-01

摘要: 大规模数据中心需要消耗大量的电能,由此带来了高额的运营成本以及环境污染等问题。为了降低数据中心的能耗,在构造了数据中心管理模型的基础上,提出了虚拟机静态安置算法与动态调整算法。虚拟机的动态迁移技术能够有效地降低数据中心能耗,提升资源利用率。然而,过度地迁移虚拟机,会影响应用的运行质量,造成SLA违背。动态调整阶段,采用了动态阈值的方法来控制虚拟机的迁移,降低能耗。最后,利用CloudSim平台进行了大量的模拟实验。实验结果表明,所提出的数据中心虚拟机节能管理机制(EAMVM)能够降低能源消耗,减少虚拟机的迁移次数。

关键词: 能耗,虚拟机,动态阈值,动态迁移

Abstract: Large scale data centers need to consume a large amount of power,resulting in high operating costs and other issues such as environmental pollution.In order to reduce the energy consumption of the data center,we constructed a management model of the data center and proposed the algorithm of the static placement algorithm and dynamic adjustment of the virtual machine.Dynamic migration of virtual machine can effectively reduce the energy consumption while improving resource utilization.However,excessive migration of virtual machines will affect the quality of the application and cause SLA violation.In the dynamic adjustment stage,we adopted dynamic thresholds to control the virtual machine migration and reduce energy consumption.Finally,we used CloudSim to do a lot of experiments.The results show that the energy-aware management of virtual machine (EAMVM) mechanism can reduce energy consumption and reduce the number of virtual machine migration. 〖BHDWG1,WK42,WK43,WK42W〗第10期 朱德剑 ,等:数据中心虚拟机节能管理机制

Key words: Energy consumption,Virtual machines,Dynamic thresholds,Live migrations

[1] State of the Data Center 2011 [EB/OL].[2016-08-05].http://www.emersonnetworkpower.com/en-US/Solutions/infographics/Pages/2011DataCenterState.aspx.
[2] YE K J,WU Z H,JIANG X H,et al.Power Management ofVirtualized Cloud Computing Platform[J].Chinese Journal of Computers,2012,35(6):1262-1285.(in Chinese) 叶可江,吴朝晖,姜晓红,等.虚拟化云计算平台的能耗管理[J].计算机学报,2012,35(6):1262-1285.
[3] DONG Y,ZHOU L,JIN Y,et al.Improving Energy Efficiency for Mobile Media Cloud via Virtual Machine Consolidation[J].Mobile Networks and Applications,2015,20(3):370-379.
[4] HIEU N T,DI FRANCESCO M,JSKI A Y.A virtual machine placement algorithm for balanced resource utilization in cloud data centers[C]∥2014 IEEE 7th International Conference on Cloud Computing.IEEE,2014:474-481.
[5] HUANG Z N,LI H S,ZHAO J.Virtual Machine Placement Algorithm Based on Improved Genetic Algorithm[J].Computer Science,2015,2(S2):406-407,416.(in Chinese) 黄兆年,李海山,赵君.基于双适应度遗传算法的虚拟机放置的研究[J].计算机科学,2015,2(S2):406-407,416.
[6] ZHU X,YOUNG D,WATSON B J,et al.1000 islands:Integratedcapacity and workload management for the next generation data center[C]∥International Conference on Autonomic Computing,2008(ICAC’08).IEEE,2008:172-181.
[7] ADHIKARI J,PATIL S.Double threshold energy aware load balancing in cloud computing[C]∥2013 Fourth International Conference on Computing,Communications and Networking Technologies (ICCCNT).IEEE,2013:1-6.
[8] BELOGLAZOV A,BUYYA R.Adaptive threshold-based ap-proach for energy-efficient consolidation of virtual machines in cloud data centers[C]∥Proceedings of the 8th International Workshop on Middleware for Grids,Clouds and e-Science.ACM,2010:1-6.
[9] BEATY K A,BOBROFF N,KOCHUT A.Dynamic placement of virtual machines for managing violations of service level agreements(SLAs):U.S.Patent 8,1,411[P].2012-10-16.
[10] TANG Z,MO Y,LI K,et al.Dynamic forecast scheduling algorithm for virtual machine placement in cloud computing environment[J].The Journal of Supercomputing,2014,70(3):1279-1296.
[11] FAN X,WEBER W D,BARROSO L A.Power provisioning for a warehouse-sized computer[C]∥International Symposium on Computer Architecture(DBLP).2007:13-23
[12] XU F,LIU F,LIU L,et al.iaware:Making live migration of virtual machines interference-aware in the cloud[J].IEEE Tran-sactions on Computers,2014,63(12):3012-3025.
[13] BELOGLAZOV A,BUYYA R.Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers[J].Concurrency and Computation:Practice and Ex-perience,2012,24(13):1397-1420.
[14] FU X,ZHOU C.Virtual machine selection and placement for dynamic consolidation in Cloud computing environment[J].Frontiers of Computer Science,2015,9(2):322-330.
[15] CALHEIROS R N,RANJAN R,BELOGLAZOV A,et al.CloudSim:a toolkit for modeling and simulation of cloud computing environments and evaluation of resource provisioning algorithms[J].Software:Practice and Experience,2011,41(1):23-50.
[16] SPECpower_ssj2008 Results [EB/OL].[2016-08-05].http://www.spec.org/power_ssj2008/results.

No related articles found!
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!