Quantitative Evaluation of Cloud Elasticity based on Fuzzy Analytic Hierarchy Process

Elasticity is one of the most important cloud computing characteristics, which enables deployed applications to dynamically adapt to workload-changing demands by acquiring and releasing shared computing resources at runtime. However, the existing cloud elasticity metrics are either oversimplified or hard to use, thereby lacking a comprehensive evaluation mech-anism to properly compare the elastic feature among different cloud providers. To address this gap, we propose an assessment method for cloud elasticity based on fuzzy hierarchical analysis. We use a fuzzy hierarchical model to quantitatively assess the qualitative metrics with a unified standard model. We compare three public cloud providers (Ali Cloud, HUAWEI Cloud, Tencent Cloud) as case studies and measure their cloud elasticity based on the proposed model on a cluster. To verify the effectiveness of our method, we also measure three cloud platforms using auto scaling performance metrics proposed by SPEC Cloud Group. The results show that our proposed elasticity quantification method is feasible.