Design and performance evaluation of a distributed teaching resource scheduling system integrating 5G and cloud computing

With the rapid development of 5G communication technology and cloud computing architecture, smart education has placed higher demands on the dynamic scheduling and efficient distribution of teaching resources. Traditional teaching resource scheduling systems often suffer from low resource utilization, high response latency, and poor system scalability when faced with large-scale concurrent access and complex network environments. This paper designs a distributed teaching resource scheduling system integrating 5G and cloud computing, constructing an “edge-cloud” collaborative resource service architecture. By combining task characteristics and network status, it proposes an efficient scheduling algorithm and execution mechanism. The system achieves flexible deployment and dynamic scaling of teaching resources through a microservice architecture, and utilizes edge computing nodes to achieve low-latency service responses, effectively improving the distribution efficiency and system stability of teaching resources. Through performance testing in a simulated teaching environment, this paper verifies the significant advantages of this system in key metrics such as resource utilization, response time, and task completion rate, providing technical support and a reference model for new smart education platforms.