Federated learning using game strategies: State-of-the-art and future trends
R Gupta, J Gupta - Computer Networks, 2023 - Elsevier
Federated learning (FL) is a new and promising paradigm that allows devices to learn
without sharing data with the centralized server. It is often built on decentralized data where …
without sharing data with the centralized server. It is often built on decentralized data where …
Empowering digital twin for future networks with graph neural networks: Overview, enabling technologies, challenges, and opportunities
As the complexity and scale of modern networks continue to grow, the need for efficient,
secure management, and optimization becomes increasingly vital. Digital twin (DT) …
secure management, and optimization becomes increasingly vital. Digital twin (DT) …
Incentive-based federated learning for digital-twin-driven industrial mobile crowdsensing
Mobile crowdsensing has empowered the Industrial Internet of Things (IIoT) in many ways,
such as vehicle-aided traffic flow scheduling, drone-aided visual inspections, etc. However …
such as vehicle-aided traffic flow scheduling, drone-aided visual inspections, etc. However …
Computation offloading and resource allocation based on DT-MEC-assisted federated learning framework
Traditional centralized machine learning uses a large amount of data for model training,
which may face some privacy and security problems. On the other hand, federated learning …
which may face some privacy and security problems. On the other hand, federated learning …
Resource Efficient Federated Learning and DAG Blockchain With Sharding in Digital Twin Driven Industrial IoT
L Jiang, Y Liu, H Tian, L Tang… - IEEE Internet of Things …, 2024 - ieeexplore.ieee.org
The development of Industry 4.0 relies on emerging technologies of digital twin, machine
learning, blockchain, and Internet of Things (IoT) to build autonomous self-configuring …
learning, blockchain, and Internet of Things (IoT) to build autonomous self-configuring …
RCFL: Redundancy-Aware Collaborative Federated Learning in Vehicular Networks
In vehicular networks (VNets), vehicular federated learning (VFL) is a new learning
paradigm that can protect data privacy of vehicle nodes (VNs) while training models. In VFL …
paradigm that can protect data privacy of vehicle nodes (VNs) while training models. In VFL …
When autonomous vehicles meet accidents: A DT-enabled post-accident maintenance scheme
The autonomous vehicles (AVs), as intelligent mobile robots, can undertake tasks to
facilitate various computation-intensive services in intelligent transportation system (ITS) …
facilitate various computation-intensive services in intelligent transportation system (ITS) …
Resources-efficient Adaptive Federated Learning for Digital Twin-Enabled IIoT
Digital twin (DT) can bridge the physical status with the virtual space in real-time for the
Industrial Internet of Things (IIoT), where the integration of federated learning (FL) with DT …
Industrial Internet of Things (IIoT), where the integration of federated learning (FL) with DT …
Multi-tasking federated learning meets blockchain to foster trust and security in the Metaverse
H Moudoud, S Cherkaoui - Ad Hoc Networks, 2023 - Elsevier
The Metaverse is a term that refers to a shared virtual space where users can interact with
each other and with a virtual environment in real-time. The Metaverse has gained a lot of …
each other and with a virtual environment in real-time. The Metaverse has gained a lot of …
Deep reinforcement learning based vehicle selection for asynchronous federated learning enabled vehicular edge computing
In the traditional vehicular network, computing tasks generated by the vehicles are usually
uploaded to the cloud for processing. However, since task offloading toward the cloud will …
uploaded to the cloud for processing. However, since task offloading toward the cloud will …