A Data Congestion Control Method for Wireless Mobile Networks Based on Load Prediction
For wireless networks in mobile communication systems,current congestion control methods often deploy data transmission and processing nodes in a single target mode,where each node only focuses on its own target task,resulting in low control efficiency and high data packet loss rate.Therefore,this study designs a new data congestion control method for wireless mobile networks based on load prediction results.Firstly,based on the current congestion control requirements,a multi-level approach is adopted to deploy congestion control nodes.Secondly,construct a congestion control model based on the network load prediction results.Finally,Deep Q-Leaning Network(DQN)assisted processing is adopted to control network data congestion.The test results show that compared to traditional control methods,the method proposed in this paper has higher data throughput and a data packet loss rate controlled below 1.5％,indicating that the method proposed in this paper has practical application value.
load forecastingwireless mobile networknetwork datacongestion controlcontrol methoddata integration
万方数据
维普
