A Hybrid Approach for Virtual Machine Migration in Cloud Computing Environment

Ramandeep Kaur

Abstract


A lot of research has been done in the field of cloud computing in computing domain.  For its effective performance, variety of algorithms has been proposed. The role of virtualization is significant and its performance is dependent on VM Migration and allocation. More of the energy is absorbed in cloud; therefore, the utilization of numerous algorithms is required for saving energy and efficiency enhancement in the proposed work. In the proposed work, green algorithm has been considered with meta heuristic algorithms, ABC (Artificial Bee colony .Every server has to perform different or same functions. A cloud computing infrastructure can be modelled as Primary Machineas a set of physical Servers/host PM1, PM2, PM3… PMn. The resources of cloud infrastructure can be used by the virtualization technology, which allows one to create several VMs on a physical server or host and therefore, lessens the hardware amount and enhances the resource utilization. The computing resource/node in cloud is used through the virtual machine. To address this problem, data centre resources have to be managed in resource -effective manner for driving Green Cloud computing that has been proposed in this work using Virtual machine concept with ABC and Neural Network optimization algorithm. The simulations have been carried out in CLOUDSIM environment and the parameters like SLA violations, Energy consumption and VM migrations along with their comparison with existing techniques will be performed.

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References


R. Buyya, R. Ranjan and R. N. Calheiros, “Modeling and simulation of scalable Cloud computing environments and the CLOUDSIM toolkit: Challenges and opportunities,” 2009 International Conference on High Performance Computing & Simulation, Leipzig, 2009, pp. 1-11.

Xu, Gaochao, et al. “A novel artificial bee colony approach of live virtual machine migration policy using Bayes theorem.” The Scientific World Journal 2013.

Hashizume, Keiko, et al. “An analysis of security issues for cloud computing.” Journal of Internet Services and Applications 4.1 (2013): 5.

M. Satyanarayanan, P. Bahl, R. Caceres and N. Davies, “The Case for VM-Based Cloudlets in Mobile Computing,” in IEEE Pervasive Computing, vol. 8, no. 4, pp. 14-23, Oct.-Dec. 2009.

Voorsluys, W., Broberg, J., Venugopal, S., &Buyya, R. (2009). Cost of Virtual Machine Live Migration in Clouds: A Performance Evaluation. CloudCom, vol.9, pp.254-265.

O. Osanaiye, S. Chen, Z. Yan, R. Lu, K. K. R. Choo and M. Dlodlo, “From Cloud to Fog Computing: A Review and a Conceptual Live VM Migration Framework,” in IEEE Access, vol. 5, no. , pp. 8284-8300, 2017.

T. G. Rodrigues, K. Suto, H. Nishiyama and N. Kato, “Hybrid Method for Minimizing Service Delay in Edge Cloud Computing Through VM Migration and Transmission Power Control,” in IEEE Transactions on Computers, vol. 66, no. 5, pp. 810-819, May 1 2017.

Y. Wen, Z. Li, S. Jin, C. Lin and Z. Liu, “Energy-Efficient Virtual Resource Dynamic Integration Method in Cloud Computing,” in IEEE Access, vol. 5, no. , pp. 12214-12223, 2017.

C. Xu, Z. Zhao, H. Wang, R. Shea and J. Liu, “Energy Efficiency of Cloud Virtual Machines: From Traffic Pattern and CPU Affinity Perspectives,” in IEEE Systems Journal, vol. 11, no. 2, pp. 835-845, June 2017.

Zhang, Qi, Lu Cheng, and RaoufBoutaba. “Cloud computing: state-of-the-art and research challenges.” Journal of internet services and applications vol.1, 2010, pp. 7-18.

Buyya, Rajkumar, Rajiv Ranjan, and Rodrigo N. Calheiros. “Intercloud: Utility-oriented federation of cloud computing environments for scaling of application services.” International Conference on Algorithms and Architectures for Parallel Processing. Springer, Berlin, Heidelberg, 2010.

Z. Xiao, W. Song and Q. Chen, “Dynamic Resource Allocation Using Virtual Machines for Cloud Computing Environment,” in IEEE Transactions on Parallel and Distributed Systems, vol. 24, no. 6, pp. 1107-1117, June 2013.

Qiang Li, QinfenHao, Limin Xiao, and Zhoujun Li, “Adaptive Management of Virtualized Resources in Cloud Computing Using Feedback Control,” in First International Conference on Information Science and Engineering, April 2009, pp. 99-102.

Sarathe, Reena, Amit Mishra, and Shiv Kumar Sahu. “Max-Min Ant System based Approach for Intelligent VM Migration and Consolidation for Green Cloud Computing.” International Journal of Computer Applications vol.136, 2016.

Goudarzi H., Pedram M., “Multi-dimensional SLA-based Resource Allocation for Multi-tier Cloud Computing Systems,” in IEEE International Conference on Cloud Computing, Sep. 2011, pp. 324- 331.

Bo Li, Jianxin Li, JinpengHuai, TianyuWo, Qin Li,LiangZhong (2009), “EnaCloud:AnEnegy-saving Application Live Placement Approach for Cloud Computing Enviorments” , In IEEE International Conference on cloud Computing 2009, pp. 17-24.

Jiandun Li, JunjiePeng, Wu Zhang (2011), “A Scheduling Algorithm for Private Clouds”, Journal of Convergence Information Technology, Vol. 6, pp.1-9.




DOI: https://doi.org/10.23956/ijarcsse.v7i9.407

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