Continuing Education Network Data Center Model Based on Fractional Differential Mathematical Equations

Abstract

Abstract Continuing education platforms are faced with problems such as the aging of online learning platforms and backward technology. The data center network is an essential infrastructure supporting the big data and cloud computing platform continuing education network. It is widely used for data-intensive and massively parallel computing tasks. The paper proposes a continuing education network data center management model based on this research background. At the same time, this paper proposes a real-time encryption method for distributed data in a multi-layer differential continuing education network based on fractional differential mathematical equations. The experimental study found that the fractional differential mathematical equations method can effectively control the stability of data transmission of continuing education receipt networks. This algorithm improves the efficiency of network data operation and controls the cost of encryption. The research results of this paper provide technical support for network education.