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Cooperative Schemes for Joint Latency and Energy Consumption Minimization in UAV-MEC Networks

Author(s): Cheng M; He S; Pan Y; Lin M; Zhu WP;

The Internet of Things (IoT) has promoted emerging applications that require massive device collaboration, heavy computation, and stringent latency. Unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) systems can provide flexible services for user devices (UDs) with wide coverage. The optimization of both latency and energy consumption rema ...

Article GUID: 40942666


Trust-Augmented Deep Reinforcement Learning for Federated Learning Client Selection

Author(s): Rjoub G; Wahab OA; Bentahar J; Cohen R; Bataineh AS;

In the context of distributed machine learning, the concept of federated learning (FL) has emerged as a solution to the privacy concerns that users have about sharing their own data with a third-party server. FL allows a group of users (often referred to as clients) to locally train a single machine learning model on their devices without sharing their ra ...

Article GUID: 35875592


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