DocumentCode
173033
Title
Virtual Numbers for Virtual Machines?
Author
Tan, Alan Y. S. ; Ko, Ryan K. L. ; Mendiratta, Veena
Author_Institution
Dept. of Comput. Sci., Univ. of Waikato, Hamilton, New Zealand
fYear
2014
fDate
June 27 2014-July 2 2014
Firstpage
972
Lastpage
974
Abstract
Knowing the number of virtual machines (VMs) that a cloud physical hardware can (further) support is critical as it has implications on provisioning and hardware procurement. However, current methods for estimating the maximum number of VMs possible on a given hardware is usually the ratio of the specifications of a VM to the underlying cloud hardware´s specifications. Such naive and linear estimation methods mostly yield impractical limits as to how many VMs the hardware can actually support. It was found that if we base on the naive division method, user experience on VMs at those limits would be severely degraded. In this paper, we demonstrate through experimental results, the significant gap between the limits derived using the estimation method mentioned above and the actual situation. We believe for a more practicable estimation of the limits of the underlying infrastructure, dominant workload of VMs should also be factored in.
Keywords
cloud computing; virtual machines; VM specifications; cloud computing; cloud hardware specifications; cloud physical hardware; cloud resource provisioning; hardware procurement; linear estimation methods; naive division method; virtual machines; virtual numbers; virtualization; Cloud computing; Estimation; Hardware; Random access memory; Servers; Usability; Virtual machining; cloud computing; cloud resource provisioning; load limit prediction; virtualization;
fLanguage
English
Publisher
ieee
Conference_Titel
Cloud Computing (CLOUD), 2014 IEEE 7th International Conference on
Conference_Location
Anchorage, AK
Print_ISBN
978-1-4799-5062-1
Type
conf
DOI
10.1109/CLOUD.2014.147
Filename
6973853
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