DocumentCode :
2980013
Title :
A VM-based Resource Management Method Using Statistics
Author :
Zhenzhong Zhang ; Limin Xiao ; Yongnan Li ; Li Ruan
Author_Institution :
State Key Lab. of Software Dev. Environ., Beihang Univ., Beijing, China
fYear :
2012
fDate :
17-19 Dec. 2012
Firstpage :
788
Lastpage :
793
Abstract :
Virtualization technology is one of the key technologies in cloud computing. Proper allocation of the virtual machines onto available hosts plays an important role on the performance optimization of cloud computing. At present, many resource management methods are based on the load model to predict the resource requirements of the application. However, a variety of heterogeneous hardware environments and virtualization technologies make it hard to efficiently allocate the resources based on existing methods. To address the problem, we proposed a virtual machine allocation strategy based on statistics. And The contribution of this paper include:(1) A load-resource model for estimating the resource demand of each virtual machine, (2) An algorithm for assigning virtual machines onto the hosts among resource pool according to the resources requirement of virtual machine. Experiments show that our load-resource model can accurately estimate the resource requirements of virtual machines for physical host, and our virtual machine assigning algorithm can achieve better load balancing compared with the first-fit and best-fit algorithm.
Keywords :
cloud computing; optimisation; statistical analysis; virtual machines; VM based resource management method; cloud computing; hardware environments; load resource model; performance optimization; statistics; virtual machines; virtualization technology; Computational modeling; Load modeling; Prediction algorithms; Predictive models; Resource management; Virtual machining; Virtualization; Cloud Computing; Load balancing; Virtual Machine Allocation Strategy; Virtual machine performance modeling;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel and Distributed Systems (ICPADS), 2012 IEEE 18th International Conference on
Conference_Location :
Singapore
ISSN :
1521-9097
Print_ISBN :
978-1-4673-4565-1
Electronic_ISBN :
1521-9097
Type :
conf
DOI :
10.1109/ICPADS.2012.128
Filename :
6413604
Link To Document :
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