A hybrid task offloading and resource allocation approach for digital twin-empowered UAV-assisted MEC network using federated reinforcement learning for future …

P Consul, I Budhiraja, D Garg, N Kumar… - IEEE Transactions …, 2024 - ieeexplore.ieee.org
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 …

[HTML][HTML] Federated reinforcement learning based task offloading approach for MEC-assisted WBAN-enabled IoMT

P Consul, I Budhiraja, R Arora, S Garg, BJ Choi… - Alexandria Engineering …, 2024 - Elsevier
The exponential proliferation of wearable medical apparatus and healthcare information
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

P Consul, I Budhiraja, D Garg - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
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 reassessing in UAV-assisted cyber-physical systems based on federated learning

P Consul, I Budhiraja, R Chaudhary… - MILCOM 2022-2022 …, 2022 - ieeexplore.ieee.org
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 …

FLBCPS: Federated learning based secured computation offloading in blockchain-assisted cyber-physical systems

P Consul, I Budhiraja, R Chaudhary… - 2022 IEEE/ACM 15th …, 2022 - ieeexplore.ieee.org
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 …

Federated learning based trajectory optimization for UAV enabled MEC

A Nehra, P Consul, I Budhiraja, G Kaur… - ICC 2023-IEEE …, 2023 - ieeexplore.ieee.org
We present a moving mobile edge computing architecture in which unmanned aerial
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

P Consul, I Budhiraja, D Garg, S Garg… - Vehicular …, 2024 - Elsevier
The convergence of mobile edge computing (MEC) network with unmanned aerial vehicles
(UAVs) presents an auspicious opportunity to revolutionize wireless communication and …

Data-driven techniques and security issues in wireless networks

MM Saeed, ES Ali, RA Saeed - Data-Driven Intelligence in …, 2023 - taylorfrancis.com
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 …

Deep Reinforcement Learning Based Reliable Data Transmission Scheme for Internet of Underwater Things in 5G and Beyond Networks

P Consul, I Budhiraja, D Garg - Procedia Computer Science, 2024 - Elsevier
Abstract The Internet of Underwater Things (IoUT) is an interconnected communication
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

P Consul, I Budhiraja, D Garg - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The computationally intensive tasks generated by AIoTD face challenges due to its
limitations in battery power and computing capabilities. These devices typically operate in …