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Scientific Programming
Volume 2016, Article ID 7519507, 13 pages
Research Article

On Elasticity Measurement in Cloud Computing

1College of Information Science and Engineering, Hunan University, Changsha, Hunan 410082, China
2IBM Massachusetts Lab, 550 King Street, Littleton, MA 01460, USA
3Department of Computer Science, State University of New York, New Paltz, NY 12561, USA
4Department of Computing and Information Systems, University of Melbourne, Melbourne, VIC 3010, Australia

Received 21 January 2016; Accepted 8 May 2016

Academic Editor: Florin Pop

Copyright © 2016 Wei Ai et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Elasticity is the foundation of cloud performance and can be considered as a great advantage and a key benefit of cloud computing. However, there is no clear, concise, and formal definition of elasticity measurement, and thus no effective approach to elasticity quantification has been developed so far. Existing work on elasticity lack of solid and technical way of defining elasticity measurement and definitions of elasticity metrics have not been accurate enough to capture the essence of elasticity measurement. In this paper, we present a new definition of elasticity measurement and propose a quantifying and measuring method using a continuous-time Markov chain (CTMC) model, which is easy to use for precise calculation of elasticity value of a cloud computing platform. Our numerical results demonstrate the basic parameters affecting elasticity as measured by the proposed measurement approach. Furthermore, our simulation and experimental results validate that the proposed measurement approach is not only correct but also robust and is effective in computing and comparing the elasticity of cloud platforms. Our research in this paper makes significant contribution to quantitative measurement of elasticity in cloud computing.