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Classified scheduling algorithm of big data under cloud computing

ABSTRACT In order to realize the optimization of resource scheduling in the cloud computing environment and improve the utilization ratio of network data resource, we need to carry out the data resource scheduling in the cloud computing environment. But when using the current scheduling method for data resource scheduling in cloud computing environment, we schedule the current task through determining the resource scheduling cost function, however, we do not take into account the comprehensive evaluation cost of performance of user data, resulting in data network resource scheduling is poor. Therefore, this paper proposed a method of scheduling network data resources in cloud computing environment based on particle swarm optimization. Firstly, this method dynamically clusters cloud computing network data resources. By considering the network bandwidth, the bandwidth utilization, the current network running state, the method introduces the particle swarm apportion model in the process of building the network data resource scheduling model, and predicts the execution speed of task based on network nodes, and schedules and arranges task sets of different data resources. We obtain the total weight of data network resource scheduling tasks and take it as parameters to calculate the fitness value, on the basis of particle swarm optimization algorithm, we optimize different network data resource scheduling tasks. Experimental results show that the proposed method is suitable for the scheduling of network data resources in cloud computing environment, and has advantages in scheduling efficiency and resource utilization.