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.
Highlights
We have evaluated cloud elasticity values using two methods, that is, (1) the elasticity values in terms of the steady-state probabilities obtained for the given parameter and (2) the elasticity values in terms of our simulation system obtained for the same parameters
The virtual machine start-up rate is assigned the value of α = 120 virtual machines (VMs)/hour, and the virtual machine shut-off rate is assigned the value of β = 540 VMs/hour
We have introduced a new definition of cloud elasticity
Summary
A cloud computing platform relies on the virtualization technique to acquire more VMs to deal with workload surges or release VMs to avoid resource overprovisioning. Such a dynamic resource provision and management feature is called elasticity. We are motivated to develop a comprehensive model and an analytical method to measure cloud elasticity. We propose a clear and concise definition to compute elasticity value. The proposed computing model can quantify, measure, and compare the elasticity of cloud platforms. The model is an analytical method, and an easy way to calculate the elasticity value of a cloud platform quantitatively.
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