Applications of Distributed Machine Learning for the Internet-of-Things: A Comprehensive Survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
Applications of distributed machine learning for the Internet-of-Things: A comprehensive survey
The emergence of new services and applications in emerging wireless networks (eg,
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
beyond 5G and 6G) has shown a growing demand for the usage of artificial intelligence (AI) …
pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization
due to data heterogeneity in an ever domain-shifting environment. While Federated …
due to data heterogeneity in an ever domain-shifting environment. While Federated …
Collaborative policy learning for dynamic scheduling tasks in cloud-edge-terminal IoT networks using federated reinforcement learning
In this article, we examine cloud–edge–terminal Internet of Things (IoT) networks, where
edges undertake a range of typical dynamic scheduling tasks. In these IoT networks, a …
edges undertake a range of typical dynamic scheduling tasks. In these IoT networks, a …
Federated learning with NOMA assisted by multiple intelligent reflecting surfaces: Latency minimizing optimization and auction
Federated learning (FL) has emerged as a promising framework to exploit massive data
generated by edge devices in developing a common learning model while preserving the …
generated by edge devices in developing a common learning model while preserving the …
Federated Learning–Based Model to Lightweight IDSs for heterogeneous IoT Networks: State-of-the-Art, Challenges and Future Directions.
A large number of Internet of Things (IoT) devices have been deployed in numerous
applications (eg, smart homes, healthcare, smart grids, manufacturing processes, and …
applications (eg, smart homes, healthcare, smart grids, manufacturing processes, and …
Joint Resource and Trajectory optimization for Energy Efficiency maximization in UAV-Based networks
The explosive growth of unmanned aerial vehicles (UAVs)-based networks has accelerated
in recent years. One of the crucial tasks of a UAV-based network is managing and allocating …
in recent years. One of the crucial tasks of a UAV-based network is managing and allocating …
ACF: An Adaptive Compression Framework for Multimodal Network in Embedded Devices
The ubiquitous Internet-of-Things (IoT) devices generate vast amounts of multimodal data,
and the deep multimodal fusion network (DMFN) is a promising technology for processing …
and the deep multimodal fusion network (DMFN) is a promising technology for processing …
A multifaceted survey on federated learning: Fundamentals, paradigm shifts, practical issues, recent developments, partnerships, trade-offs, trustworthiness, and ways …
A Majeed, SO Hwang - IEEE Access, 2024 - ieeexplore.ieee.org
Federated learning (FL) is considered a de facto standard for privacy preservation in AI
environments because it does not require data to be aggregated in some central place to …
environments because it does not require data to be aggregated in some central place to …
HGNN: A Hierarchical Graph Neural Network Architecture for Joint Resource Management in Dynamic Wireless Sensor Networks
During the flourishing era of the Internet of Things (IoTs), wireless sensor networks (WSNs)
have emerged as a critical backbone for sensing, connectivity, and automation in 6G …
have emerged as a critical backbone for sensing, connectivity, and automation in 6G …