Beyond the edge: An advanced exploration of reinforcement learning for mobile edge computing, its applications, and future research trajectories

N Yang, S Chen, H Zhang… - … Communications Surveys & …, 2024 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) broadens the scope of computation and storage beyond the
central network, incorporating edge nodes close to end devices. This expansion facilitates …

Client scheduling for multiserver federated learning in industrial iot with unreliable communications

H Zhao, Y Tan, K Guo, W **a, B Xu… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The Industrial Internet of Things (IIoT) is emerging as a promising technology that can
accelerate the application of industrial intelligence to smart factories. Because of the …

Optimal directed acyclic graph federated learning model for energy-efficient IoT communication networks

G Nalinipriya, EL Lydia, SR Sree, D Nikolenko… - Scientific Reports, 2024 - nature.com
Federated learning (FL) stimulates distributed on-device computation systems to process an
optimum technique efficiency by communicating local process upgrades and global method …

Towards Seamless Hierarchical Federated Learning under Intermittent Client Participation: A Stagewise Decision-Making Methodology

M Wu, M Liwang, Y Su, L Li, S Hosseinalipour… - arxiv preprint arxiv …, 2025 - arxiv.org
Federated Learning (FL) offers a pioneering distributed learning paradigm that enables
devices/clients to build a shared global model. This global model is obtained through …

ENERGY-EFFICIENT USER-EDGE ASSOCIATION AND RESOURCE ALLOCATION IN IOT-BASED HIERARCHICAL FEDERATED LEARNING

HA SAADAT - 2022 - qspace.qu.edu.qa
The proliferation of data as part of the Internet of Things (IoT) systems needs to be efficiently
utilized while respecting data privacy and scalability. Edge computing is an emerging …