Networks Traffic Prediction Based on LSTM

The rapid advancement of communication technologies, driven by the widespread adoption of 5G/6G, IoT, and cloud computing, has led to explosive growth in network traffic. This surge often results in network congestion, poor quality of service. To address these challenges, accurate network traffic prediction becomes important for enabling efficient resource allocation and ensuring high-level service quality. This paper proposes a network traffic prediction method based on the Long Short-Term Memory (LSTM) model. The simulation results demonstrate the effectiveness of the LSTM-based approach in predicting network traffic.