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Found 3 papers, 1 papers with code
Attentive Federated Learning for Concept Drift in Distributed 5G Edge Networks
Machine learning (ML) is expected to play a major role in 5G edge computing.
A Fast Edge-Based Synchronizer for Tasks in Real-Time Artificial Intelligence Applications
The cluster of devices use a late notification protocol to select the best point among the pre-computed synchronization points to reach a time aligned task execution as quickly as possible.
Using Machine Learning for Handover Optimization in Vehicular Fog Computing
We further propose the use of this predictive system in a smarter request routing mechanism to minimize the service interruption during handovers between fog nodes and to anticipate areas of low coverage through a series of experiments and test the models' performance on a test set.
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