An Optimal Resource Provisioning Algorithm for Cloud Computing Environment

Abstract

Resource Provisioning in a Cloud Computing Environment ensures flexible and dynamic access of the cloud resources to the end users. The Multi-Objective Decision Making approach considers assigning priorities to the decision alternatives in the environment. Each alternative represents a cloud resource defined in terms of various characteristics termed as decision criteria. The provisioning objectives refer to the heterogeneous requirements of the cloud users. This research study proposes a Resource Interest Score Evaluation Optimal Resource Provisioning (RISE-ORP) algorithm which uses Analytical Hierarchy Process (AHP) and Ant Colony Optimization (ACO) as a unified MOMD approach to design an optimal resource provisioning system. It uses AHP as a method to rank the cloud resources for provisioning. The ACO is used to examine the cloud resources for which resource traits best satisfy the provisioning. The performance of this approach is analyzed using CloudSim. The experimental results show that our approach offers improvement in the performance of previously used AHP approach for resource provisioning.