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Resource-aware virtual machine placement algorithm for IaaS cloud

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Abstract

Cloud computing is an on-demand Internet-based computing service, where computing resources are shared among the users via the Internet and its usage based on the pay-for-use model. Virtualization of computing resources allows the system to use the resources efficiently. One of the challenging issues in virtualization is the placement of virtual machine (VM) on the physical machines (PMs) in order to utilize computing resources efficiently. Furthermore, imbalanced usage of resources also leads to overall resource wastage of an IaaS cloud. In this paper, we propose a new VM placement algorithm called RVMP for IaaS cloud. The first objective of the proposed algorithm is to minimize the power consumption of the IaaS cloud by reducing the number of active PMs. We devise a new technique called resource usage factor to place a VM on a suitable PM so that resources of the PM can utilize efficiently. The second objective is to minimize the unbalanced utilization of resources among the active PMs. We propose a new resource usage model by which one can successfully figure out unbalanced utilization of resources on the active PMs. By using the proposed model, we adopt a limited migration of VMs to minimize the unbalanced utilization of resources. Finally, the proposed algorithm is compared with the existing algorithms in terms of various performance metrics. The simulation results demonstrate the superior performance of the proposed algorithm.

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References

  1. Buyya R, Yeo CS, Venugopal S, Broberg J, Brandic I (2009) Cloud computing and emerging IT platforms: vision, hype, and reality for delivering computing as the 5th utility. Future Gener Comput Syst 25(6):599–616

    Article  Google Scholar 

  2. Lombardi F, Di Pietro R (2011) Secure virtualization for cloud computing. J Netw Comput Appl 34(4):1113–1122

    Article  Google Scholar 

  3. Zhang Q, Cheng L, Boutaba R (2010) Cloud computing: state-of-the-art and research challenges. J Internet Serv Appl 1(1):7–18

    Article  Google Scholar 

  4. Komu M, Sethi M, Mallavarapu R, Oirola H, Khan R, Tarkoma S (2012) Secure networking for virtual machines in the cloud. In: Proceedings of IEEE International Conference on Cluster Computing Workshops, pp 88–96

  5. Davidovic V, IIijevic D, Luk V, Pogarcic I (2015) Private cloud computing and delegation of control. Procedia Eng 100:196–205

    Article  Google Scholar 

  6. Srinivasan A, Quadir MA, Vijayakumar V (2015) Era of cloud computing: a new insight to hybrid cloud. Procedia Comput Sci 50:42–51

    Article  Google Scholar 

  7. Zhang Q, Li M, Hu X (2014) Network traffic-aware virtual machine placement with availability guarantees based on shadows. In: Proceedings of 14th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CCGrid), pp 542–543

  8. Masdari M, Nabavi SS, Ahmadi V (2016) An overview of virtual machine placement schemes in cloud computing. J Netw Comput Appl 66:106–127

    Article  Google Scholar 

  9. Cardosa M, Korupolu M, Singh A (2009) Shares and utilities based power consolidation in virtualized server environments. In: Proceedings of IFIP/IEEE Integrated Network Management, pp 327–334

  10. Grit L, Irwin D, Yumerefendi A, Chase J (2006) Virtual machine hosting for networked clusters: building the foundations for autonomic orchestration. In: Proceedings of 1st International Workshop on Virtualization Technology in Distributed Computing, pp 7–7

  11. Khanna G, Beaty K, Kar G, Kochut A (2006) Application performance management in virtualized server environments. In: Proceedings of 10th IEEE/IFIP Network Operations and Management Symposium (NOMS), pp 373–381

  12. Dosa G, Li R, Han X, Tuza Z (2013) Tight absolute bound for first fit decreasing bin-packing. Theor Comput Sci 510:13–61

    Article  MATH  Google Scholar 

  13. Wang J, Huang S, Ju W, He Y, Wang H, Zhang J, Gu W (2012) Best fit decreasing based defragmentation algorithm in semi-dynamic elastic optical path networks. In: Proceedings of Asia Communications and Photonics Conference (ACP), pp 1–3

  14. Stillwell M, Schanzenbach D, Vivien F, Casanova H (2010) Resource allocation algorithms for virtualized service hosting platforms. J Parallel Distrib Comput 70(9):962–974

    Article  MATH  Google Scholar 

  15. Xu J, Fortes JAB (2010) Multi-objective virtual machine placement in virtualized data center environments. In: Proceedings of IEEE/ACM International Conference on Cyber, Physical and Social Computing, Green Computing and Communications, pp 179–188

  16. Gao Y, Guan H, Qi Z, Hou Y, Lu L (2013) A multi-objective ant colony system algorithm for virtual machine placement in cloud computing. J Comput Syst Sci 79(8):1230–1242

    Article  MathSciNet  MATH  Google Scholar 

  17. Huang W, Li X, Qian Z (2013) An energy-efficient virtual machine placement algorithm with balanced resource utilization. In: Proceedings of 7th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS), pp 313–319

  18. Li X, Qian Z, Chi R, Zhang B, Lu S (2012) Balancing resource utilization for continuous virtual machine requests in clouds. In: Proceedings of 6th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing, IMIS, pp 266-273

  19. Li X, Qian Z, Lu S, Wu J (2013) Energy efficient virtual machine placement algorithm with balanced and improved resource utilization in a data center. J Math Comput Model 58(5–6):1222–1235

    Article  MathSciNet  Google Scholar 

  20. Mohan Raj VK, Shriram R (2016) Power management in virtualized data center—a survey. J Netw Comput Appl 69:117–133

    Article  Google Scholar 

  21. 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. J Concurr Comput 24(13):1397–1420

    Article  Google Scholar 

  22. Gupta MK, Amgoth T (2016) Resource-aware algorithm for virtual placement in cloud Environment. In: Proceedings of 9th IEEE International Conference on Contemporary Computing (IC3), India, pp 1–6

  23. Dai X, Wang JM, Bensaou B (2014) Energy-efficient virtual machine placement in data centers with heterogeneous requirements. In: Proceedings of 3rd International Conference on Cloud Networking (CloudNet), pp 161–166

  24. Wang S, Liu Z, Zheng Z, Sun Q, Yang F (2013) Particle swarm optimization for energy-aware virtual machine placement optimization in virtualized data centers. In: Proceedings of International Conference on Parallel and Distributed Systems (ICPADS), pp 102–109

  25. Zheng Q, Li R, Li X, Shah N, Zhang J, Tian F, Chao KM, Li J (2016) Virtual machine consolidated placement based on multi-objective biogeography-based optimization. Future Gener Comput Syst 54:95–122

    Article  Google Scholar 

  26. Feller E, Rilling L, Morin C (2011) Energy-aware ant colony based workload placement in clouds. In: Proceedings of IEEE/ACM 12th International Conference on Grid Computing, pp 26–33

  27. 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(5):755–768

    Article  Google Scholar 

  28. Esfandiarpoor S, Pahlavan A, Goudarzi M (2015) Structure-aware online virtual machine consolidation for datacenter energy improvement in cloud computing. Comput Electr Eng 42:74–89

    Article  Google Scholar 

  29. Panda SK, Jana PK (2015) Efficient task scheduling algorithms for heterogeneous multi-cloud environment. J Supercomput 71(4):1505–1533

    Article  Google Scholar 

  30. Panda SK, Jana PK (2016) Normalization-based task scheduling algorithms for heterogeneous multi-cloud environment. Inf Syst Front. doi:10.1007/s10796-016-9683-5

    Google Scholar 

  31. Amazon (2015) Amazon EC2 instance types, http://aws.amazon.com/ec2/instance-types/, (Last access 13 Feb 2015)

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Correspondence to Tarachand Amgoth.

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Gupta, M.K., Amgoth, T. Resource-aware virtual machine placement algorithm for IaaS cloud. J Supercomput 74, 122–140 (2018). https://doi.org/10.1007/s11227-017-2112-9

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  • DOI: https://doi.org/10.1007/s11227-017-2112-9

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