Abstract

Cloud computing is a novel paradigm that aims to provision on-demand computing capacities as services. Virtualization is an important technology integrated in Cloud Computing. Mapping the virtual machines to the appropriate physical machines is called VM placement. The effectiveness and elasticity of virtual machine placement has become the main concern in cloud computing environments. Effective placement of virtual machines is important for optimization of computational resources and reduction of the probability of virtual machine reallocation. This paper provides a survey and brief analysis of some of the main VM Placement mechanism utilized in cloud computing.

References

• Zhou, Z., Hu, Z., & Li, K. (2016). Virtual Machine Placement Algorithm for Both Energy-Awareness and SLA Violation Reduction in Cloud Data Centers. Scientific Programming, 2016, 1-11. doi:10.1155/2016/5612039
• Calcavecchia, N. M., Biran, O., Hadad, E., & Moatti, Y. (2012). VM Placement Strategies for Cloud Scenarios. 2012 IEEE Fifth International Conference on Cloud Computing. doi:10.1109/cloud.2012.113
• Thiruvenkadam, T., & Kamalakkannan, P. (2015). Energy Efficient Multi-Dimensional Host Load Aware Algorithm for Virtual Machine Placement and Optimization in Cloud Environment. Indian Journal of Science and Technology, 8(17). doi:10.17485/ijst/2015/v8i17/59140
• Zhou, Z., Hu, Z., Song, T., & Yu, J. (2015). A novel virtual machine deployment algorithm with energy efficiency in cloud computing. Journal of Central South University, 22(3), 974-983. doi:10.1007/s11771-015-2608-5
• Ma, F., Liu, F., & Liu, Z. (2012). Distributed load balancing allocation of virtual machine in cloud data center. 2012 IEEE International Conference on Computer Science and Automation Engineering. doi:10.1109/icsess.2012.6269396
• Sheikhalishahi, M., Wallace, R. M., Grandinetti, L., Vazquez-Poletti, J. L., & Guerriero, F. (2016). A multi-dimensional job scheduling. Future Generation Computer Systems, 54, 123-131. doi:10.1016/j.future.2015.03.014
• Amarante, S. R., Roberto, F. M., Cardoso, A. R., & Celestino, J. (2013). Using the Multiple Knapsack Problem to Model the Problem of Virtual Machine Allocation in Cloud Computing. 2013 IEEE 16th International Conference on Computational Science and Engineering. doi:10.1109/cse.2013.77
• Bin-Packing. (n.d.). SpringerReference. doi:10.1007/springerreference_5277
• Malviya, P., Agrawal, S., & Singh, S. (2014). An Effective Approach for Allocating VMs to Reduce the Power Consumption of Virtualized Cloud Environment. 2014 Fourth International Conference on Communication Systems and Network Technologies. doi:10.1109/csnt.2014.121
• Ni, J., Huang, Y., Luan, Z., Zhang, J., & Qian, D. (2011). Virtual machine mapping policy based on load balancing in private cloud environment. 2011 International Conference on Cloud and Service Computing. doi:10.1109/csc.2011.6138536
• Hamdi, K., & Kefi, M. (2016). Network-aware virtual machine placement in cloud data centers: An overview. 2016 International Conference on Industrial Informatics and Computer Systems (CIICS). doi:10.1109/iccsii.2016.7462398
• Chowdhury, M. R., Mahmud, M. R., & Rahman, R. M. (2015). Study and performance analysis of various VM placement strategies. 2015 IEEE/ACIS 16th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing (SNPD). doi:10.1109/snpd.2015.7176234
• Masdari, M., Nabavi, S. S., & Ahmadi, V. (2016). An overview of virtual machine placement schemes in cloud computing. Journal of Network and Computer Applications, 66, 106-127. doi:10.1016/j.jnca.2016.01.011
• 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. Mathematical and Computer Modelling, 58(5-6), 1222-1235. doi:10.1016/j.mcm.2013.02.003
• Li, K., Zheng, H., & Wu, J. (2013). Migration-based virtual machine placement in cloud systems. 2013 IEEE 2nd International Conference on Cloud Networking (CloudNet). doi:10.1109/cloudnet.2013.6710561
• Usmani, Z., & Singh, S. (2016). A Survey of Virtual Machine Placement Techniques in a Cloud Data Center. Procedia Computer Science, 78, 491-498. doi:10.1016/j.procs.2016.02.093
• Pires, F. L., Melgarejo, E., & Baran, B. (2013). Virtual machine placement. A multi-objective approach. 2013 XXXIX Latin American Computing Conference (CLEI). doi:10.1109/clei.2013.6670671
• Choudhary, A., Rana, S., & Matahai, K. (2016). A Critical Analysis of Energy Efficient Virtual Machine Placement Techniques and its Optimization in a Cloud Computing Environment. Procedia Computer Science, 78, 132-138. doi:10.1016/j.procs.2016.02.022
• Zheng, X., & Cai, Y. (2014). Dynamic Virtual Machine Placement for Cloud Computing Environments. 2014 43rd International Conference on Parallel Processing Workshops. doi:10.1109/icppw.2014.28
• Mills, K., Filliben, J., & Dabrowski, C. (2011). Comparing VM-Placement Algorithms for On-Demand Clouds. 2011 IEEE Third International Conference on Cloud Computing Technology and Science. doi:10.1109/cloudcom.2011.22.
• Zeng, H., Zeng, H., He, T., & Zhang, N. (2013). Virtual machine placement and optimization for data center. Journal of Computer Applications, 33(10), 2772-2777. doi:10.3724/sp.j.1087.2013.02772