MultiGran-STGCNFog fuses multi-granular spatiotemporal features in a GCN and uses a genetic-algorithm scheduler to pipeline inference across heterogeneous fog devices, reporting up to 9.86% accuracy improvement and 2.43x throughput gain on PEMS datasets.
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Forecasting at Full Spectrum: Holistic Multi-Granular Traffic Modeling under High-Throughput Inference Regimes
MultiGran-STGCNFog fuses multi-granular spatiotemporal features in a GCN and uses a genetic-algorithm scheduler to pipeline inference across heterogeneous fog devices, reporting up to 9.86% accuracy improvement and 2.43x throughput gain on PEMS datasets.