An HFL framework with edge-generated synthetic data and an evolutionary game for worker edge selection improves accuracy under non-IID data, but the uniqueness and stability proofs are not rigorous.
Dynamic Edge Association and Resource Allocation in Self-Organizing Hierarchical Federated Learning Networks,
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Edge Association Strategies for Synthetic Data Empowered Hierarchical Federated Learning with Non-IID Data
An HFL framework with edge-generated synthetic data and an evolutionary game for worker edge selection improves accuracy under non-IID data, but the uniqueness and stability proofs are not rigorous.