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Digital-Twin-Enabled 6G: Vision, Architectural Trends, and Future Directions
Therefore, enabling IoE applications over 6G requires a new framework that can be used to manage, operate, and optimize the 6G wireless system and its underlying IoE services.
Edge-computing
Networking and Internet Architecture
Federated Learning for Internet of Things: Recent Advances, Taxonomy, and Open Challenges
However, given the presence of massively distributed and private datasets, it is challenging to use classical centralized learning algorithms in the IoT.
Networking and Internet Architecture
Dispersed Federated Learning: Vision, Taxonomy, and Future Directions
However, federated learning still has privacy concerns due to sensitive information inferring capability of the aggregation server using end-devices local learning models.
Distributed, Parallel, and Cluster Computing
Federated Learning for Edge Networks: Resource Optimization and Incentive Mechanism
IoT devices with intelligence require the use of effective machine learning paradigms.
Distributed, Parallel, and Cluster Computing
