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 production …
entities such as manufacturers and suppliers to train global models for optimizing production …
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 …
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 …
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 …
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 …
TCV-D: An Approach for Path Selection in Vehicular Task Offloading
N Keshari, D Singh - Vehicular Communications, 2024 - Elsevier
The vehicular task offloading technology enhances the transportation system by offloading
tasks of task-requesting vehicles (TRV) to either vehicular fog nodes (VFN) or road-side …
tasks of task-requesting vehicles (TRV) to either vehicular fog nodes (VFN) or road-side …
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 …
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 …
SMITS: Social and Mobility aware Intelligent Task Scheduling in Vehicular Fog Computing—A Federated DRL Approach
Vehicular fog computing (VFC) has become an enticing research hot spot to provide
resources for the Internet of Vehicles (IoV) application requests. Moreover, with the massive …
resources for the Internet of Vehicles (IoV) application requests. Moreover, with the massive …
Data Collection Algorithms for Model Training in Internet of Vehicles
In Internet of Vehicles (IoV), it is critical to collect sufficient data for model training, to support
vehicular intelligent applications. However, the environment of IoV is highly dynamic due to …
vehicular intelligent applications. However, the environment of IoV is highly dynamic due to …