TA-STGAT: A Spatio-Temporal Graph Attention Network for Edge-State Prediction in Vehicular Edge Computing
Experimental results show that, compared with the best-performing baseline in terms of RMSE for each forecasting task, TA-STGAT reduces RMSE by 10.89% and 11.29% in workload-representation prediction and traffic flow prediction, respectively, demonstrating its effectiveness for short-term edge-state forecasting.