Virtual Machine consolidation policy for power usage management in cloud data centers
- DOI
- 10.2991/ameii-16.2016.168How to use a DOI?
- Keywords
- Virtual Machine consolidation, Energy efficiency, Cloud computing, virtual machine migration
- Abstract
In Today's world, IT technologies are growing day by day so the need of computing and storage are growing with it. The increasing of cloud services demands requires more computing resources to fulfill the end user's requirements. So, energy consumption by cloud computing resources is also increasing day by day and become a key problem in cloud environment. In cloud computing, data centers consume huge amount of energy and also emit carbon dioxide in the environment. For energy optimization, energy efficient resource management is required. In this paper a novel approach is presented to manage the power usage of virtual machines by introducing a dynamic programming algorithm that would be responsible for the selection of the best virtual machines that would cater for the migration from an overloaded physical machine. In order to identify the overloaded physical machines, underloaded physical machines and how many of them have no tasks; the ratio of occupied resources is calculated using MIPS, RAM and Bandwidth. Optimally selection of Virtual Machines and place them on appropriate host lead to minimize energy consumption.
- Copyright
- © 2016, 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 - Rugwiro Ulysse AU - Chunhua Gu PY - 2016/04 DA - 2016/04 TI - Virtual Machine consolidation policy for power usage management in cloud data centers BT - Proceedings of the 2nd International Conference on Advances in Mechanical Engineering and Industrial Informatics (AMEII 2016) PB - Atlantis Press SP - 865 EP - 871 SN - 2352-5401 UR - https://doi.org/10.2991/ameii-16.2016.168 DO - 10.2991/ameii-16.2016.168 ID - Ulysse2016/04 ER -