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A hybrid task offloading and resource allocation approach for digital twin-empowered UAV-assisted MEC network using federated reinforcement learning for future …
Federated learning (FL) is proposed as a different approach for distributed learning on the
edges while maintaining privacy. Existing FL methods, are mainly focused on learning deep …
edges while maintaining privacy. Existing FL methods, are mainly focused on learning deep …
[HTML][HTML] Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT
The exponential proliferation of wearable medical apparatus and healthcare information
within the framework of the Internet of Medical Things (IoMT) introduces supplementary …
within the framework of the Internet of Medical Things (IoMT) introduces supplementary …
A hybrid secure resource allocation and trajectory optimization approach for mobile edge computing using federated learning based on WEB 3.0
The use of unmanned aerial vehicles (UAVs) in Internet-of-Things (IoT) has grown, but
security for UAV communications still a challenge due to the distributed nature of line-of …
security for UAV communications still a challenge due to the distributed nature of line-of …
Security reassessing in UAV-assisted cyber-physical systems based on federated learning
Mobile-edge computing (MEC) is a popular method for increasing the quality of computing
experience for consumers since it allows them to offload computing operations to MEC …
experience for consumers since it allows them to offload computing operations to MEC …
FLBCPS: Federated learning based secured computation offloading in blockchain-assisted cyber-physical systems
Mobile-edge computing (MEC) is a in demand method for improving the quality of
computation experience on mobile devices (MD) since it helps MD's to offload computing …
computation experience on mobile devices (MD) since it helps MD's to offload computing …
Federated learning based trajectory optimization for UAV enabled MEC
We present a moving mobile edge computing architecture in which unmanned aerial
vehicles (UAV) serve as an equipment, providing computational power and allowing task …
vehicles (UAV) serve as an equipment, providing computational power and allowing task …
SFL-TUM: Energy efficient SFRL method for large scale AI model's task offloading in UAV-assisted MEC networks
The convergence of mobile edge computing (MEC) network with unmanned aerial vehicles
(UAVs) presents an auspicious opportunity to revolutionize wireless communication and …
(UAVs) presents an auspicious opportunity to revolutionize wireless communication and …
Data-driven techniques and security issues in wireless networks
The data-Driven Technique is a method that employs real-world data to acquire insight into
system behavior. It allows for the examination of small, simple systems as well as large …
system behavior. It allows for the examination of small, simple systems as well as large …
Deep Reinforcement Learning Based Reliable Data Transmission Scheme for Internet of Underwater Things in 5G and Beyond Networks
Abstract The Internet of Underwater Things (IoUT) is an interconnected communication
ecosystem for underwater devices in maritime environments. IoUT devices range from …
ecosystem for underwater devices in maritime environments. IoUT devices range from …
Task Offloading in AIoT-Enabled UAV-Assisted MEC Network: A Digital Twin-Empowered Approach With FedRL
The computationally intensive tasks generated by AIoTD face challenges due to its
limitations in battery power and computing capabilities. These devices typically operate in …
limitations in battery power and computing capabilities. These devices typically operate in …