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A dynamic VM consolidation technique for QoS and energy consumption in cloud environment

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An Erratum to this article was published on 01 June 2017

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Abstract

Cloud-based data centers consume a significant amount of energy which is a costly procedure. Virtualization technology, which can be regarded as the first step in the cloud by offering benefits like the virtual machine and live migration, is trying to overcome this problem. Virtual machines host workload, and because of the variability of workload, virtual machines consolidation is an effective technique to minimize the total number of active servers and unnecessary migrations and consequently improves energy consumption. Effective virtual machine placement and migration techniques act as a key issue to optimize the consolidation process. In this paper, we present a novel virtual machine consolidation technique to achieve energy–QoS–temperature balance in the cloud data center. We simulated our proposed technique in CloudSim simulation. Results of evaluation certify that physical machine temperature, SLA, and migration technique together control the energy consumption and QoS in a cloud data center.

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  • 01 June 2017

    An erratum to this article has been published.

References

  1. Mell P, Grance T (2011) The NIST definition of cloud computing. http://csrc.nist.gov/publications/nistpubs/800-145/SP800-145.pdf. Accessed 15 Nov 2016

  2. Amazon EC2. https://aws.amazon.com/ec2/

  3. Zhu X, Young D, Watson BJ, Wang Z, Rolia J, Singhal S, McKee B et al (2008) 1000 islands: an integrated approach to resource management for virtualized data centers. Clust Comput 12:45–57

    Article  Google Scholar 

  4. Meng X, Isci C, Kephart J, Zhang L, Bouillet E, Pendarakis D (2010) Efficient resource provisioning in compute clouds via VM multiplexing. In: Proceeding of the 7th International Conference on Autonomic Computing

  5. America’s Data Centers Are Wasting Huge Amounts of Energy. https://www.nrdc.org/sites/default/files/data-center-efficiency-assessment-IB.pdf

  6. Asad Z, Chaudhry MAR (2016) A two-way street: green big data processing for a greener smart grid. IEEE Syst J 99:1–11

    Google Scholar 

  7. Cardosa M, Korupolu MR, Singh A (2009) Shares and utilities based power consolidation in virtualized server environments. In: IFIP/IEEE International Symposium on Integrated Network Management

  8. Beloglazov A, Buyya R (2012) Optimal online deterministic algorithms and adaptive heuristics for energy and performance efficient dynamic consolidation of virtual machines in cloud data centers. Concurr Comput Pract Exp 24:1397–1420

    Article  Google Scholar 

  9. Cao Z, Dong S (2014) An energy-aware heuristic framework for virtual machine consolidation in cloud computing. J Supercomput 69:429–451

    Article  Google Scholar 

  10. Deng W, Liu F, Jin H, Liao X, Liu H (2013) Reliability-aware server consolidation for balancing energy-lifetime tradeoff in virtualized cloud datacenters. Int J Commun Syst. doi:10.1002/dac.2687

    Google Scholar 

  11. Younge AJ, von Laszewski G, Wang L, Lopez-Alarcon S, Carithers W (2010) Efficient resource management for cloud computing environments. In: International Conference on Green Computing

  12. Arianyan E, Taheri H, Sharifian S (2015) Novel heuristics for consolidation of virtual machines in cloud data centers using multi-criteria resource management solutions. J Supercomput 72:688–717

    Article  Google Scholar 

  13. Beloglazov A, Abawajy J, Buyya R (2012) Energy-aware resource allocation heuristics for efficient management of data centers for cloud computing. Future Gener Comput Syst 28:755–768

    Article  Google Scholar 

  14. Yang CT, Liu JC, Huang KL, Jiang FC (2014) A method for managing green power of a virtual machine cluster in cloud. Future Gener Comput Syst 37:26–36

    Article  Google Scholar 

  15. Li X, Ventresque A, Murphy J, Thorburn J (2014) SOC: satisfaction-oriented virtual machine consolidation in enterprise data centers. Int J Parallel Progr 44:130–150

    Article  Google Scholar 

  16. Hwang I, Pedram M (2016) Hierarchical, portfolio theory-based virtual machine consolidation in a compute cloud. IEEE Trans Serv Comput 99:1

    Article  Google Scholar 

  17. Mastroianni C, Meo M, Papuzzo G (2013) Probabilistic consolidation of virtual machines in self-organizing cloud data centers. IEEE Trans Cloud Comput 1:215–228

    Article  Google Scholar 

  18. Farahnakian F, Ashraf A, Pahikkala T, Liljeberg P, Plosila J, Porres I, Tenhunen H (2015) Using ant colony system to consolidate vms for green cloud computing. IEEE Trans Serv Comput 8:187–198

    Article  Google Scholar 

  19. Beloglazov A, Buyya R (2013) Managing overloaded hosts for dynamic consolidation of virtual machines in cloud data centers under quality of service constraints. IEEE Trans Parallel Distrib Syst 24:1366–1379

    Article  Google Scholar 

  20. Karthik C, Sharma M, Maurya K, Chandrasekaran K (2016) Green intelligence for cloud data centers. In: 3rd International Conference on Recent Advances in Information Technology (RAIT)

  21. Zola E, Kassler AJ (2016) Optimising for energy or robustness? Trade-offs for VM consolidation in virtualized datacenters under uncertainty. Optim Lett. doi:10.1007/s11590-016-1065-x

  22. Wu Q, Ishikawa F (2015) Heterogeneous virtual machine consolidation using an improved grouping genetic algorithm. In: IEEE 17th International Conference on High Performance Computing and Communications. doi:10.1109/HPCC-CSS-ICESS.2015.92

  23. Lee EK, Viswanathan H, Pompili D (2015) Proactive thermal-aware resource management in virtualized HPC cloud datacenters. IEEE Trans Cloud Comput 99:1

    Article  Google Scholar 

  24. Wang JV, Cheng CT, Chi KT (2015) A power and thermal-aware virtual machine allocation mechanism for Cloud data centers. In: IEEE International Conference on Communication Workshop (ICCW). doi:10.1109/ICCW.2015.7247611

  25. Xu F, Liu F, Liu L, Jin H, Li B, Li B (2014) iAware: making live migration of virtual machines interference-aware in the cloud. IEEE Trans Comput 63:3012–3025

    Article  MathSciNet  MATH  Google Scholar 

  26. Standard Performance Evaluation Corporation. https://www.spec.org/power_ssj2008/results/

  27. Buyya R, Ranjan R, Calheiros RN (2009) Modeling and simulation of scalable cloud computing environments and the CloudSim toolkit: challenges and opportunities. In: International Conference on High Performance Computing & Simulation. doi:10.1109/HPCSIM.2009.5192685

  28. Amazon EC2 Instance Types. https://aws.amazon.com/ec2/instance-types/

  29. Park KS, Pai VS (2006) a mostly-scalable monitoring system for PlanetLab. ACM SIGOPS Oper Syst Rev 40:65–74

    Article  Google Scholar 

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Authors and Affiliations

  1. Department of Computer Engineering, Islamic Azad University Science and Research Branch, Tehran, Iran

    Seyed Yahya Zahedi Fard & Sahar Adabi

  2. Department of Information Technology, Iran Telecommunication Research Center, Tehran, Iran

    Mohamad Reza Ahmadi

Authors
  1. Seyed Yahya Zahedi Fard
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  2. Mohamad Reza Ahmadi
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  3. Sahar Adabi
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Corresponding author

Correspondence to Seyed Yahya Zahedi Fard.

Additional information

An erratum to this article is available at https://doi.org/10.1007/s11227-017-2079-6.

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Zahedi Fard, S.Y., Ahmadi, M.R. & Adabi, S. A dynamic VM consolidation technique for QoS and energy consumption in cloud environment. J Supercomput 73, 4347–4368 (2017). https://doi.org/10.1007/s11227-017-2016-8

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  • DOI: https://doi.org/10.1007/s11227-017-2016-8

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