Efficient Split Federated Learning for Resource-Constrained Heterogeneous Wireless Devices

The proposed Efficient Split Federated Learning (ESFL) algorithm significantly improves the training efficiency of Split Federated Learning by jointly optimizing user-side workload and server-side computing resource allocation under resource-constrained heterogeneous wireless environments.