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Energy Efficient Virtual Machine Placement in Data Center
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 182 - Number 29 |
| Year of Publication: 2018 |
| Authors: Ashwini S. Bhujbal, Pranoti C. Bansode, Pallavi P. Dukale, Sayali S. Gaikwad, N. R. Shikalgar |
10.5120/ijca2018918155
|
Ashwini S. Bhujbal, Pranoti C. Bansode, Pallavi P. Dukale, Sayali S. Gaikwad, N. R. Shikalgar . Energy Efficient Virtual Machine Placement in Data Center. International Journal of Computer Applications. 182, 29 ( Nov 2018), 25-28. DOI=10.5120/ijca2018918155
Abstract
The rising trend of e-commerce and cloud computing are just two reasons for the growing demand for Data Centers (DCs). DCs are among the largest global energy consumers in relation to the total global energy consumption. The rising numbers of DCs are an increasingly negative impact on the environment. This may be caused by the DCs themselves as well as by the power generation that is needed by the DCs. Thus, the utilization of servers in most data centers can be improved by adding virtualization and selecting the most suitable host for each Virtual Machine (VM). The problem of VM placement is an optimization problem to achieve multiple goals. To overcome those problems we design the allocator in order to accept as many VM requests as possible, taking into account the power consumption of the network devices. It can be covered through various approaches such as allocator policy (Best Fit/Worst Fit), allocation strategy (Single/Multi-objective optimization), and network resources. Each approach aims to simultaneously reduce power consumption, maximize resource utilization and avoid traffic congestion.
References
- C.-T. Yang, K.-C. Wang, H.-Y. Cheng, C.-T. Kuo, and W. C. C. Chu, “Green Power Management with Dynamic Resource Allocation for Cloud Virtual Machines.” IEEE, Sep. 2016, pp. 726–733. [Online]. Available: http://ieeexplore.ieee.org/document/6063066/
- S. R. M. Amaranth, F. M. Roberto, A. R. Cardoso, and J. Celestino, “Using the Multiple Knapsack Problem to Model the Problem of Virtual Machine Allocation in Cloud Computing.” IEEE, Dec. 2015, pp. 476– 483. [Online]. Available: http://ieeexplore.ieee.org/document/6755257/.
- J. Xu and J. A. B. Fortes, “Multi-objective virtual machine placement in virtualized data center environments,” in Green Computing and Communications (GreenCom), 2016 IEEE/ACM Int’l Conference on Int’l Conference on Cyber, Physical and Social Computing (CPSCom), Dec 2016, pp. 179–188.
- C. Ghribi, M. Hadji, and D. Zeghlache, “Energy efficient vm scheduling for cloud data centers: Exact allocation and migration algorithms,” in 2016 13th IEEE/ACM International Symposium on Cluster, Cloud, and Grid Computing, May 2016, pp. 671–678.
- D. Minarolli and B. Freisleben, “Virtual machine resource allocation in cloud computing via multi-agent fuzzy control,” in Cloud and Green Computing (CGC), 2016 Third International Conference on, Sept 2016, pp. 188–194.
- G. Portaluri, S. Giordano, D. Kliazovich, and B. Dorronsoro, “A power efficient genetic algorithm for resource allocation in cloud computing data centers,” in Cloud Networking (CloudNet), 2015 IEEE 3rd International Conference on, Oct 2015, pp. 58–63.
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