Learning based energy efficient task offloading for vehicular collaborative edge computing

P Qin, Y Fu, G Tang, X Zhao… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
Extensive delay-sensitive and computation-intensive tasks are involved in emerging
vehicular applications. These tasks can hardly be all processed by the resource constrained …

Task offloading and trajectory control for UAV-assisted mobile edge computing using deep reinforcement learning

L Zhang, ZY Zhang, L Min, C Tang, HY Zhang… - IEEE …, 2021 - ieeexplore.ieee.org
Mobile Edge Computing (MEC) has been widely employed to support various Internet of
Things (IoT) and mobile applications. By leveraging the advantages of easily deployed and …

BARGAIN-MATCH: A game theoretical approach for resource allocation and task offloading in vehicular edge computing networks

Z Sun, G Sun, Y Liu, J Wang… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is emerging as a promising architecture of vehicular
networks (VNs) by deploying the cloud computing resources at the edge of the VNs …

Urllc-awared resource allocation for heterogeneous vehicular edge computing

Q Wu, W Wang, P Fan, Q Fan, J Wang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Vehicular edge computing (VEC) is a promising technology to support real-time vehicular
applications, where vehicles offload intensive computation tasks to the nearby VEC server …

[HTML][HTML] QoS-SLA-aware adaptive genetic algorithm for multi-request offloading in integrated edge-cloud computing in Internet of vehicles

H Materwala, L Ismail, HS Hassanein - Vehicular Communications, 2023 - Elsevier
Abstract The Internet of Vehicles over vehicular ad hoc network is an emerging technology
enabling the development of smart applications focused on improving traffic safety, traffic …

DRL-based URLLC-constraint and energy-efficient task offloading for internet of health things

Y Wang, H Wu, RH Jhaveri… - IEEE Journal of …, 2023 - ieeexplore.ieee.org
Internet of Health Things (IoHT) is a promising e-Health paradigm that involves offloading
numerous computational-intensive and delay-sensitive tasks from locally limited IoHT points …

Distributed clustering-based cooperative vehicular edge computing for real-time offloading requests

J Wang, K Zhu, B Chen, Z Han - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Mobile vehicles have been considered as potential edge servers to provide computation
resources for the emerging Intelligent Transportation System (ITS) applications. However …

pfedlvm: A large vision model (lvm)-driven and latent feature-based personalized federated learning framework in autonomous driving

WB Kou, Q Lin, M Tang, S Xu, R Ye, Y Leng… - arXiv preprint arXiv …, 2024 - arxiv.org
Deep learning-based Autonomous Driving (AD) models often exhibit poor generalization
due to data heterogeneity in an ever domain-shifting environment. While Federated …

Handover-enabled dynamic computation offloading for vehicular edge computing networks

H Maleki, M Başaran… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
The computation offloading technique is a promising solution that empowers
computationally limited resource devices to run delay-constrained applications efficiently …

Cost-and energy-efficient aerial communication networks with interleaved hovering and flying

N Babu, M Virgili, CB Papadias… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
This work proposes a methodology for the energy-and cost-efficient 3-D deployment of an
unmanned aerial vehicle (UAV)-based aerial access point (AAP), that exchanges a given …