Optimal Cloud Resource Selection Method Considering Hard and Soft Constraints and Multiple Conflicting Objectives
Courtney Powell, Katsunori Miura, Masaharu Munetomo · 2018
This paper proposes a method for selecting optimal cloud resource configurations that satisfy hard and soft user constraints and multiple conflicting objectives. In the proposed method, feasible configurations generation and optimal configurations selection are carried out as two separate and independent processes that execute either sequentially or concurrently depending on the level of complexity of the optimization problem and the size of its solution space. The feasible configurations generation process utilizes an equivalent transformation-based constraint satisfaction method to generate the universe of feasible resource configurations that satisfy user requirements and constraints for a given cloud resource selection problem. In the optimal resource configurations selection process, nondominated sorting, reference points association, and niching/elitism are performed to produce a user-specified number of diverse Pareto-optimal configurations from the feasible resource configurations universe. The results of application of the proposed method to (1) a three-tier web application and (2) a cloud-based workflow resource allocation scenario verify its efficacy.