Resource Scheduling Management System of Container Cloud Platform based on Virtualization Technology

With the rapid development of cloud computing services. The number of containers in the container cloud platform is increasing rapidly, but the resource allocation response speed of the server is slow, and the resource scheduling is unreasonable. To solve this problem, a resource scheduling management system of container cloud platform is proposed. The resource usage prediction is carried out by using the combination of back-propagation neural network and differential autoregressive moving average model. Adaptive scaling module and real-time resource scheduling module are introduced into the scheduling system. The experimental outcomes indicate that the prediction error of the combined model is the smallest, 14.07 and 27.43 lower than that of other methods, and the prediction root-mean-square error is the largest 1.02. The resource utilization index of the resource balancing scheduling algorithm is 0.30, 0.22, 0.18 and 0.10 lower than that of other algorithms, respectively. It can be concluded that the combined model can effectively improve the prediction accuracy of resource usage and improve the prediction accuracy. The resource balancing scheduling algorithm can quickly schedule resources according to real-time requirements, effectively improve the resource balance and resource utilization, and enhance the user experience. This study provides a reference for the subsequent resource scheduling of container cloud platform.