Open Access Journal

ISSN : 2394-2320 (Online)

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

Open Access Journal

International Journal of Engineering Research in Computer Science and Engineering (IJERCSE)

Monthly Journal for Computer Science and Engineering

ISSN : 2394-2320 (Online)

A Review of Virtual Machine Placement algorithm in Cloud Datacenters for Server Consolidation

Author : C.Pandi Selvi 1 Dr.S.Sivakumar 2

Date of Publication :29th March 2018

Abstract: Cloud datacenters contain the number of servers, that there are some servers put in idle, as workload is distributed to all the active servers on the network called server virtualization. In order to minimize the number of active servers, we use server consolidation technique. The four major steps in server consolidation technique are namely hosted overload detection, host underload detection, virtual machine selection & migration and virtual machine placement. Virtual machine placement is the process of mapping physical machine to virtual machine for maximizing the resource utilization, minimizing energy consumption and maximizing the cloud profit. In this paper, an effective virtual machine placement algorithms and widely used approaches, parameters and optimization techniques to reduce the total energy consumption in data centers are analyzed

Reference :

    1. Ranjana R, Raja J, editors. A survey on power aware virtual machine placement strategies in a cloud data center. Green Computing, Communication and Conservation of Energy (ICGCE),2013 International Conference on; 2013: IEEE.
    2.  Varasteh A, Goudarzi M. Server consolidation techniques in virtualized data centers:IEEE Systems Journal. 2015.
    3. Ahmad RW, Gani A, Hamid SHA, Shiraz M, Yousafzai A, Xia F. A survey on virtual machine migration and server consolidation frameworks for cloud data centers. Journal of Network andComputer Applications. 2015; 52:11-25
    4. Choudhary A, Rana S, Matahai KJ. A Critical Analysis of Energy Efficient Virtual MachinePlacement Techniques and its Optimization in a Cloud Computing Environment. ProcediaComputer Science. 2016; 78:132-8.
    5. Usmani,Z and Singh,S.(2016),”A survey of virtual machine placement techniques in cloud datacenter”, Procedia computer science,78;491-498. [6] K. Halder,U. Bellur, and P. Kulkarni, “Risk aware provisioning and resource aggregation based consolidation of virtual machines,” in Proc.IEEE 5th Int. Conf. CLOUD, 2012, pp. 598–605.
    6. G. Lovász, F. Niedermeier, and H. de Meer, “Performance tradeoffs of energy-aware virtual machine consolidation,” Cluster Comput., vol. 16,no. 3, pp. 481– 496, Sep. 2013. 
    7. J. J. Prevost, K. Nagothu, B. Kelley, and M. Jamshidi, “Optimal update frequency model for physical machine state change and virtual machine placement in the cloud,” in Proc. IEEE 8th Int. Conf. SoSE, 2013,pp. 159–164
    8. T. Setzer and A. Wolke, “Virtual machine reassignment considering migration overhead,” in Proc. IEEE NOMS, 2012, pp. 631–634.
    9. V. Ebrahimirad, M.Goudarzi, and A. Rajabi, “Energy-Aware Scheduling for Precedence constrained Parallel Virtual Machines in Virtualized Data Centers,” J. Grid Comput., vol. 13, no. 2, pp. 233–253,Jun. 2015.
    10. Zhang, L., Zhuang, Y. and Zhu, W., 2013. Constraint Programming based Virtual Cloud Resources Allocation Model. International Journal of Hybrid Information Technology, 6(6), pp.333-344.
    11.  Dupont, C., Giuliani, G., Hermenier, F., Schulze, T. and Somov, A., 2012, May. An energy aware framework for virtual machine placement in cloud federated data centres. In Future Energy Systems: Where Energy, Computing and Communication Meet (e-Energy), 2012 Third International Conference on (pp. 1-10). IEEE.
    12. Dong, J., Wang, H. and Cheng, S., 2015. Energyperformance tradeoffs in IaaS cloud with virtual machine scheduling. Communications,China, 12(2), pp.155-166.

Recent Article