DocumentCode :
130882
Title :
A method of virtual machine placement based on gray correlation degree
Author :
Li He
Author_Institution :
Dept. of Inf. Sci. & Technol., Tianjin Univ. of Finance & Econ., Tianjin, China
fYear :
2014
fDate :
27-29 June 2014
Firstpage :
419
Lastpage :
424
Abstract :
Improving the utilization of resources and service qualities, and reducing the system energy consumption are two important goals of dynamic virtual machine management in cloud computing. Nevertheless, the reduction of energy consumption is inconsistent with the improvement of resource utilization. In order to get the balance, a new multi-objective decision-making method of virtual machine placement based on gray correlation degree is proposed, three factors like the energy consumption, Service Level Agreement (SLA) violation and server load are used as the evaluation indexes, and corresponding evaluation functions are biut for them, finally the multi-objective decision-making model of the virtual machine placement based on gray correlation degree is established. Evaluations via experiments show that the proposed method of virtual machine placement can achieve good results under most virtual machine selection policies.
Keywords :
cloud computing; contracts; decision making; grey systems; power aware computing; virtual machines; SLA violation; cloud computing; dynamic virtual machine management; evaluation functions; evaluation indexes; gray correlation degree; multiobjective decision-making method; resource utilization improvement; server load; service level agreement violation; service quality improvement; system energy consumption reduction; virtual machine placement; virtual machine selection policies; Cloud computing; Correlation; Decision making; Energy consumption; Indexes; Servers; Virtual machining; cloud computing; gray correlation degree; multi-objective decision-making; virtual machine placement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Software Engineering and Service Science (ICSESS), 2014 5th IEEE International Conference on
Conference_Location :
Beijing
ISSN :
2327-0586
Print_ISBN :
978-1-4799-3278-8
Type :
conf
DOI :
10.1109/ICSESS.2014.6933596
Filename :
6933596
Link To Document :
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