A Fine-Grained Performance Model of Cloud Computing Centers

Accurate performance evaluation of cloud computing resources is a necessary prerequisite for ensuring that quality of service parameters remain within agreed limits. In this paper, we employ both the analytical and simulation modeling to addresses the complexity of cloud computing systems. Analytica...

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Bibliographic Details
Published in:IEEE transactions on parallel and distributed systems 2013-11, Vol.24 (11), p.2138-2147
Main Authors: Khazaei, Hamzeh, Misic, Jelena, Misic, Vojislav B.
Format: Article
Language:English
Subjects:
Analytical models
blocking probability
Cloud computing
Computational modeling
Computer simulation
Delay
fixed-point iteration
interacting Markov model
Mathematical analysis
Mathematical models
performance analysis
Performance evaluation
Performance measurement
queuing theory
response time
Tasks
Time factors
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Summary:Accurate performance evaluation of cloud computing resources is a necessary prerequisite for ensuring that quality of service parameters remain within agreed limits. In this paper, we employ both the analytical and simulation modeling to addresses the complexity of cloud computing systems. Analytical model is comprised of distinct functional submodels, the results of which are combined in an iterative manner to obtain the solution with required accuracy. Our models incorporate the important features of cloud centers such as batch arrival of user requests, resource virtualization, and realistic servicing steps, to obtain important performance metrics such as task blocking probability and total waiting time incurred on user requests. Also, our results reveal important insights for capacity planning to control delay of servicing users requests.
ISSN:1045-9219
1558-2183
DOI:10.1109/TPDS.2012.280