Author/Authors :
Ai,Wei College of Information Science and Engineering - Hunan University, Changsha, China , Li, Kenli College of Information Science and Engineering - Hunan University, Changsha, China , Zhang, Fan IBM Massachusetts Lab, 550 King Street, Littleton, USA , Lan,Shenglin College of Information Science and Engineering - Hunan University, Changsha, China , Mei,Jing College of Information Science and Engineering - Hunan University, Changsha, China , Li, Keqin College of Information Science and Engineering - Hunan University, Changsha, China , Buyya, Rajkumar Department of Computing and Information Systems - University of Melbourne - Melbourne, V Australia
Abstract :
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.
Keywords :
Cloud Computing , Measurement , Elasticity , (CTMC) model