Multi Objective Resource Scheduling for Cloud Environment using Ant Colony Optimization Algorithm

Abstract

Cloud computing enables efficient resource sharing among several cloud users to run their applications and fulfill the business requirements. Despite the numerous advantages of cloud computing, the heterogeneity, uncertainty, and dynamic nature of user workload complicate the allocation and scheduling of cloud resources. However, improper resource allocation and scheduling result in resource waste and delays the execution of user tasks, which may volatile the Service Level Agreement (SLA). Hence, efficient resource scheduling techniques are highly desirable to maximize resource utilization and ensure efficient execution of user tasks with maintained SLA. In this Article, a multi-objective resource scheduling method is implemented to address the resource scheduling problem in a container-based cloud environment using Ant Colony Optimization algorithm (ACO). This method aims at maintaining a balance between resource utilization and efficient execution of user tasks with minimal time and cost. To evaluate the implemented method, three scenarios were conducted on ContaienrCouldSim toolkit. The experimental analysis reported that the implemented method archives high resource utilization while minimizing the makespan and execution cost in all the scenarios.