Research And Implementation Of Task Scheduling Algorithm For Cloud Computing

The concept of cloud computing comes from the concept of grid computing,parallel computing and distributed computing. It is a new business computing model.Cloud computing commercial value is huge and has a huge impact on the IT operationpattern, so cloud computing was researched by business organizations and scientificresearch institution both at home and abroad. In the cloud computing environment,users are numerous, the amount of task which the system to deal with is very huge,and cloud computing system structure is very complex. So in order to make the cloudcomputing system is fast enough to deal with the service request, meet the users’quality of service, how to efficiently scheduling tasks in the “cloud” so as to realizethe global optimization, become the key points and difficulties of cloud computingresearch.Based on task scheduling problems of the cloud computing, first of all, this paperdetailed introduction to cloud computing, task scheduling of cloud computing, particleswarm optimization algorithm and ant colony optimization algorithm. On this basis ofthe above, task scheduling algorithm based on particle swarm optimization and antcolony optimization for cloud computing (PSO-ACO) is presented in this paper. Thescheduling algorithm absorbs the fast convergence ability of particle swarmoptimization algorithm and the optimization ability of ant colony algorithm, andconsiders the cost factor. The scheduling algorithm improves the speed of the cloudcomputing task scheduling and optimization performance.Finally, we evaluate the task scheduling algorithm in cloud environment whichwas simulated by CloudSim. The result of the first experiment and the secondexperiment show that the scheduling algorithm can not only quickly find the optimalsolution, but also minimize the processing time and costs of all tasks.