Hierarchical Stochastic Models for Performance, Availability, and Power Consumption Analysis of IaaS Clouds
Abstract
Infrastructure as a Service (IaaS) is one of cloud computing’s most significant and fastest growing fields. To use the Hierarchical Stochastic Models for Performance, Availability, and Power Consumption Analysis of IaaS Clouds cloud efficiently, several important factors such as performance, availability, and power consumption need to be carefully considered and evaluated. For cost-benefit prediction and quantification of different strategies that can be applied to cloud management, evaluation of these metrics is essential.
The Hierarchical Stochastic Models for Performance, Availability, and Power Consumption Analysis of IaaS Clouds analytical-numeric results obtained from applying the proposed models to sample cloud systems show that the errors introduced by approximate models are insignificant while an improvement of several orders of magnitude is obtained in the monolithic model’s state space reduction.
System Configuration
H/W System Configuration
Speed : 1.1 GHz
RAM : 256 MB(min)
Hard Disk : 20 GB
Floppy Drive : 1.44 MB
Key Board : Standard Windows Keyboard
Mouse : Two or Three Button Mouse
Monitor : SVGA
S/W System Configuration
Platform : cloud computing
Operating system : Windows Xp,7,
Server : WAMP/Apache
Working on : Browser Like Firefox, IE
Conclusion
In this paper, we aimed to analyze the performance, availability and power consumption of IaaS cloud systems simultaneously. To achieve this, a SRN model was proposed for a cluster of PMs in a cloud data center. The proposed model captures several realistic aspects of an IaaS cloud including different pools of PMs, provisioning delays, servicing process, and PMs failure / repair behaviour.
