Optimization Algorithm for Multipath Transmission of Distance Education Resources Using Reinforcement Learning

Abstract

Distance education resources are the essential components of modern distance learning systems, and the development of high-quality resources is a potent assurance of modern distance education quality. The standard transmission efficiency assessment approach ignores the optimal data transmission stop rule and is unable to calculate the ideal stop time, resulting in excessive data transmission energy consumption and an evaluation result that does not match the real value. As a result, this study provides a reinforcement learning-based optimization technique for multipath transmission of distance education materials, because to calculate the optimal transmission rate thresholds in different detection time periods and realize the optimization of resource data transmission efficiency. According to the simulation result, the suggested efficiency optimization approach uses less energy on average and transmits data at a faster pace, improving resource data transmission efficiency. The result also shows that the proposed method performs well in terms of packet loss as compared to other existing methods.