Research On Task Scheduling Of Cloud Computing Based On Ant Colony Algorithm

Cloud computing is a new business model,which is based on the great amount of computer resources,and provides services to users in an on-demand distribution manner.Among them,task scheduling is the core of cloud computing research.How to satisfy the user's Qo S(Quality of Service),to make the resource nodes provide service and achieve load balancing effect,is the focus of the research of cloud computing task scheduling..Under the above research background,the main work is as the follows:(1)As the concept of urban weights is proposed,the ant colony algorithm is improved,then the ant colony algorithm based on urban weights is proposed,and through the simulation experiments in the TSP environment.The experimental results show that the improved algorithm jumping out of the local optimal solution capabilities is greatly enhanced;(2)The combination of ant colony algorithm and Drosophila optimization algorithm,combining their advantages,the ant colony fusion algorithm is proposed,and the performance test is carried out in the classical TSP problems.The experimental results show that the fusion algorithm and the speed is greatly improved;(3)The ant colony fusion algorithm is applied to the task scheduling system.The cloud computing task scheduling simulation system CloudSim platform is simulated and compared with the classical Min-Min algorithm and the ant colony algorithm.The experimental results show that,FOA_ACA algorithm in resource load balancing and task execution time than Min-Min algorithm and basic ant colony algorithm has been greatly improved.