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Federated Learning for Internet of Things: A Comprehensive Survey., , , , , и . IEEE Commun. Surv. Tutorials, 23 (3): 1622-1658 (2021)Federated Learning for Smart Healthcare: A Survey., , , , , , , и . ACM Comput. Surv., 55 (3): 60:1-60:37 (2023)A survey on blockchain for big data: Approaches, opportunities, and future directions., , , , , , , , и . Future Gener. Comput. Syst., (2022)Intelligent Blockchain-Based Edge Computing via Deep Reinforcement Learning: Solutions and Challenges., , , , , , , и . IEEE Netw., 36 (6): 12-19 (2022)Toward Blockchain for Edge-of-Things: A New Paradigm, Opportunities, and Future Directions., , , , , , , и . IEEE Internet Things Mag., 4 (2): 102-108 (2021)A Survey on Blockchain for Big Data: Approaches, Opportunities, and Future Directions., , , , , , , , и . CoRR, (2020)Cooperative Task Offloading and Block Mining in Blockchain-Based Edge Computing With Multi-Agent Deep Reinforcement Learning., , , , , и . IEEE Trans. Mob. Comput., 22 (4): 2021-2037 (апреля 2023)Federated Learning for COVID-19 Detection With Generative Adversarial Networks in Edge Cloud Computing., , , , и . IEEE Internet Things J., 9 (12): 10257-10271 (2022)Enabling Intelligent Traffic Steering in A Hierarchical Open Radio Access Network., , , , , , , , и . GLOBECOM, стр. 5232-5237. IEEE, (2023)Performance Evaluation of Fog-to-Cloud Computing Schemes for IoMT Systems Using Queuing Models., , , , и . GLOBECOM, стр. 1096-1100. IEEE, (2023)