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A Federated Averaging Algorithm and an optimized Federated Heterogeneous Algorithm are introduced to control the communication overhead during parameter transmission. Through an extensive case study of the Performance Measurement System (PeMS) dataset, it is shown that the FedGNN model can achieve accurate, timely traffic prediction without compromising privacy