A Novel Model for Optimizing Selection of Cloud Instance Types

With the development of cloud computing, the cloud market is becoming more and more complicated. In a cloud data center, there are many cloud instance types with different computing capacity and price, which brings users some confusions when they select cloud instance types. In order to solve this selection problem, a cloud brokering architecture is proposed. In this architecture, the selection problem is modeled as a multi-objective optimization problem, and through analysis, we get the relationship between complete Pareto set and solution space. Based on this, a two-stage Cloud Instance Type Selection Model (CITSM) is proposed to help users select the cloud instance types. The first stage is Complete Pareto Set Generation Algorithm (CPSGA) which can generate a complete Pareto set of the cloud instance type selection schemes. Then, the Optimal cloud instance type selection Scheme Screening Algorithm (OSSA) is used to select one scheme from the complete Pareto set. We perform some experiments to prove the proposed CITSM is efficient and effective. The proposed method can also solve the single objective optimization problem by modifying OSSA, which illustrates the scalability.