Implementation of Optimized Resource Allocation Algorithm in Grid Computing System

In this paper, a grid computing system based on resource optimization allocation algorithm is proposed. The system consists of four modules: grid user, grid administrator, grid resource and grid information service center. The resource allocation of the system includes two aspects: one is resource allocation on the user side, and the other is request ordering on the resource side. The two-stage optimization allows the requirements to be assigned to the most appropriate resource based on the user’s requirements. The main implementation methods of cloud computing service layer and the design of mobile Agent in the system are discussed in detail. This system can fully concentrate high-quality education resources in urban and rural areas. And through the cloud server for automatic management, to achieve the maximum degree of resource sharing. This is of great significance for improving the distribution of educational resources and public services in rural areas of China. In addition, the intelligent segmentation algorithm based on mobile agent is used to improve the intelligence of the system. Personalized learning service for users and real-time update of teaching resources are realized. The methods proposed in this paper are compared from three aspects: request completion success rate, completion time and average delay. The results fully illustrate the advantages of this system.