Admission control and scheduling algorithms based on ACO and PSO heuristic for optimizing cost in cloud computing

Abstract

Scheduling problem for user requests in cloud computing environment is NP-complete. This problem is usually solved by using heuristic methods in order to reduce to polynomial complexity. In this paper, heuristic ACO (Ant Colony Optimization) and PSO (Particle Swarm Optimization) are used to propose algorithms admission control, then building a scheduling based on the overlapping time between requests. The goal of this paper is (1) to minimize the total cost of the system, (2) satisfy QoS (Quality of Service) constraints for users, and (3) provide the greatest returned profit for SaaS providers. These algorithms are set up and run a complete test on CloudSim, the experimental results are compared with a sequential and EDF algorithms.