Research And Improvement Of Cloud Computing Resource Scheduling

Cloud computing is a new computing model in the information age,which is based on the grid,distributed and parallel computing.Cloud computing is a product of modern information technology and business services,which represent the next generation of internet technology.Resource scheduling and management is one of the key technologies in cloud computing,which mainly study how to allocate resources reasonably and how to effectively manage resource nodes with the scheduling task.Resource scheduling includes meeting the quality of customer service,improving resource utilization,load balancing,etc..Resource scheduling strategy has a direct impact on the performance of the cloud computing system and related costs.Therefore,in order to improve the matching efficiency of tasks and resources and get a better scheduling objective,it is necessary to optimize the resource scheduling scheme with various intelligent algorithms.Particle swarm is an effective search algorithm,which is based on the search process of the swarm intelligence.PSO is simple and easy to implement and it is also an efficient parallel search algorithm.Some improved particle swarm optimization algorithm is very effective in solving the problem of high complexity resource scheduling.Clustering divide the physical or abstract objects into several groups according to the similarity degree,and it has be used in many fields,such as mathematics,statistics,economics,and so on.In cloud computing resource scheduling,user task resource demand characteristic is considerable different.Based on similar to divide and conquer,optimization after user tasks clustering strategy in cloud computing resource scheduling is an effective way.This paper mainly studies the problem of resource scheduling from the following two aspects:(1)For the different task resource demanding characteristics and the heterogeneous of user tasks,this paper has researched the feasibility of task clustering strategy in user task layer.task group enhances the similarity,which effectively improve the efficiency of the subsequent task resource scheduling optimization.(2)An improved algorithm of twin particle swarm optimization is proposed.The algorithm is derived from the social progress,the conservative behavior is conducive to the stability of society,and the behavior of courage to explore can be good for social innovation.The improved algorithm can effectively improve the execution efficiency of cloud computingresource scheduling optimization.Simulation results show that,from two different layers,the task clustering strategy and improved twins particle swarm optimization algorithm applied to cloud computing resource scheduling can be effectively.The experiment has achieved satisfactory results.