Cloud computing resource scheduling based on ant colony optimization and simulated annealing algorithm

Abstract

In order to improve the utilization of cloud computing resources, this paper studies cloud computing resource scheduling based on improved Ant Colony Optimization Algorithm (ACO) and Simulated annealing algorithm (SA). We apply ACO and SA to schedule the large-scale cloud computing resource data. This paper uses SA to prevent ACO falling into the local optimal solution, and accelerate the convergence speed of ACO. The experimental results show that the proposed method is more effective compared with the already existed approaches. Our proposed method can improve the resource utilization.