For Full-Text PDF, please login, if you are a member of IEICE,|
or go to Pay Per View on menu list, if you are a nonmember of IEICE.
A New Strategy for Virtual Machine Migration Based on Decision-Theoretic Rough Sets
Hang ZHOU Qing LI Hai ZHU Jian WANG
IEICE TRANSACTIONS on Communications
Publication Date: 2018/10/01
Online ISSN: 1745-1345
Type of Manuscript: PAPER
energy conservation, SLAV, trade-off, migration, probabilistic rough sets,
Full Text: PDF(1.8MB)
>>Buy this Article
Large-scale virtualized data centers are increasingly becoming the norm in our data-intensive society. One pressing challenge is to reduce the energy consumption of servers while maintaining a high level of service agreement fulfillment. Due to the convenience of virtualization, virtual machine migration is an effective way to optimize the trade-off between energy and performance. However, there are obvious drawbacks in the current static threshold strategy for migration. This paper proposes a new decision strategy based on decision-theoretic rough sets. In the new strategy, the status of a server is determined by the Bayesian rough set model. The space is divided into positive, negative and boundary regions. According to this information, a migration decision with minimum risk will be made. This three-way decision framework in our strategy can reduce over-migration and delayed migration. The experiments in this paper show that this new strategy outperforms the benchmark examined. It is an efficient and flexible approach to the energy and performance trade-off in the cloud.