DocumentCode :
655014
Title :
Virtual Machine Placement Strategy Research
Author :
Jipeng Gao ; Gaoming Tang
Author_Institution :
Sch. of Comput. Sci. & Technol., Wuhan Univ. of Technol., Wuhan, China
fYear :
2013
fDate :
10-12 Oct. 2013
Firstpage :
294
Lastpage :
297
Abstract :
With the emergence of cloud computing, users begin to have more abstract concept for the physical machine. IaaS providers prohibits users request specify the physical machine to virtual machine resources. Users know nothing about underlying infrastructure resources. The data center carry out virtual machine placement decision-making. In this paper, we use particle swarm optimization theory to guide the placement of virtual machines in the data center resources modeling and analysis. According to user needs and current physical server load state, the algorithm quantifies each physical machine and the virtual machine´s CPU uses, memory uses, and storage uses. By using multi-objective particle swarm optimization algorithm, the placement of virtual machines based on the physical server resource utilization and the number of virtual machine migration. Simulation results show that the algorithm can effectively improve the minimum number of virtual machine migration resource utilization.
Keywords :
cloud computing; computer centres; decision making; particle swarm optimisation; resource allocation; virtual machines; IaaS providers; cloud computing; data center resources analysis; data center resources modeling; infrastructure resources; memory usage; multiobjective particle swarm optimization algorithm; physical machine; physical server load state; physical server resource utilization; storage usage; virtual machine CPU usage; virtual machine migration resource utilization; virtual machine placement decision-making; virtual machine placement strategy research; virtual machine resources; Algorithm design and analysis; Cloud computing; Particle swarm optimization; Resource management; Servers; Sociology; Virtual machining; cloud computing; resource utilization; swarm algorithm; virtual machines placement;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Cyber-Enabled Distributed Computing and Knowledge Discovery (CyberC), 2013 International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/CyberC.2013.57
Filename :
6685698
Link To Document :
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