UAV swarm cooperative target search: A multi-agent reinforcement learning approach
The development of machine learning and artificial intelligence algorithms, as well as the
progress of unmanned aerial vehicle swarm technology, has significantly enhanced the …
progress of unmanned aerial vehicle swarm technology, has significantly enhanced the …
Adaptive incentivize for cross-silo federated learning in IIoT: A multi-agent reinforcement learning approach
S Yuan, B Dong, H Lvy, H Liu, H Chen… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
In the Industrial Internet of Things (IIoT), cross-silo federated learning (CSFL) enables
entities, such as manufacturers and suppliers to train global models for optimizing …
entities, such as manufacturers and suppliers to train global models for optimizing …
Joint task offloading and resource allocation in aerial-terrestrial UAV networks with edge and fog computing for post-disaster rescue
Unmanned aerial vehicles (UAVs) are playing an increasingly important role in assisting fast-
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
response post-disaster rescue due to their fast deployment, flexible mobility, and low cost …
Multi-user layer-aware online container migration in edge-assisted vehicular networks
In edge-assisted vehicular networks, containers are very suitable for deploying applications
and providing services due to their lightweight and rapid deployment. To provide high …
and providing services due to their lightweight and rapid deployment. To provide high …
Federated split learning with data and label privacy preservation in vehicular networks
Federatedlearning (FL) is an emerging distributed learning paradigm widely used in
vehicular networks, where vehicles are enabled to train the deep model for the server while …
vehicular networks, where vehicles are enabled to train the deep model for the server while …
Digital Twin Enabled Task Offloading for IoVs: A Learning-Based Approach
This article explores the optimal offloading strategy in the Internet of Vehicles (IoVs), which is
challenged by three issues. First, the resources of edge servers are shared by multiple …
challenged by three issues. First, the resources of edge servers are shared by multiple …
Mean-field reinforcement learning for decentralized task offloading in vehicular edge computing
Abstract Vehicular Edge Computing (VEC) is a promising paradigm for providing low-latency
and high-reliability services in the Internet of Vehicles (IoV). The increasing number of …
and high-reliability services in the Internet of Vehicles (IoV). The increasing number of …
Deep Reinforcement Learning-Based Task Offloading for Vehicular Edge Computing With Flexible RSU-RSU Cooperation
W Fan, Y Zhang, G Zhou, Y Liu - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vehicle edge computing (VEC) acts as an enhancement to provide low latency and low
energy consumption for internet of vehicles (IoV) applications. Mobility of vehicles and load …
energy consumption for internet of vehicles (IoV) applications. Mobility of vehicles and load …
Optimizing Mobility-Aware Task Offloading in Smart Healthcare for Internet of Medical Things Through Multi-Agent Reinforcement Learning
In the scenario of smart healthcare applications, the Internet of Medical Things (IoMT)
devices, equipped with limited resources, would offload numerous computation-heavy tasks …
devices, equipped with limited resources, would offload numerous computation-heavy tasks …
Joint Spectrum Sharing and V2V/V2I Task Offloading for Vehicular Edge Computing Networks Based on Coalition Formation Game
M Huang, Z Shen, G Zhang - IEEE Transactions on Intelligent …, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) enables vehicles to perform computation-intensive and
delay-sensitive tasks through task offloading. Previous works either focused on task …
delay-sensitive tasks through task offloading. Previous works either focused on task …