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   Vol.E101-B   No.10   pp.2172-2185
Publication Date: 2018/10/01
Online ISSN: 1745-1345
DOI: 10.1587/transcom.2018EBP3054
Type of Manuscript: PAPER
Category: Network
energy conservation,  SLAV,  trade-off,  migration,  probabilistic rough sets,  

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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.