The Energy Optimization Based on Virtual Machine Placement
- DOI
- 10.2991/emim-17.2017.356How to use a DOI?
- Keywords
- Resource Management; Big Data; Vitalization; Energy Optimization
- Abstract
In order to solve the problem of huge energy consumption in data centers, this paper delivers a new virtual machine placement framework, including profiles and task classification. The first part of this framework is profiling phase. This phase intent to build virtual machine profiles, to identify each virtual machines run-time, resource requests, and previous utilization. The profiles are based on past virtual machine logs and coming virtual machine plans. According to these profiles, the system related to this framework will make better decisions for virtual machine placements. The second part is virtual machine classification phase. Based on some typical characteristics of virtual machines in the profiles built in last phase, the system will apart virtual machines into some given sorts. Each sort of virtual machines will have differential placement methodologies. The third part is virtual machine placement phase. All information of virtual machines, including profiles and sorts, will come to this phase. Then, the system will, accordingly, conduct typical first-fit-decrease algorithm to build a virtual machine placement plan, to enhance the power efficiency.
- Copyright
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Shoujin Wang AU - Xiaotong Cheng AU - Jingang Shi PY - 2017/04 DA - 2017/04 TI - The Energy Optimization Based on Virtual Machine Placement BT - Proceedings of the 7th International Conference on Education, Management, Information and Mechanical Engineering (EMIM 2017) PB - Atlantis Press SP - 1752 EP - 1756 SN - 2352-538X UR - https://doi.org/10.2991/emim-17.2017.356 DO - 10.2991/emim-17.2017.356 ID - Wang2017/04 ER -