Actor-critic based DRL algorithm for task offloading performance optimization in vehicle edge computing

B Wang, L Liu, J Wang - 2023 International Wireless …, 2023 - ieeexplore.ieee.org
Due to the rapid development of the Internet of Things (IoT), many latency-sensitive
application businesses have recently emerged, such as the Telematics business. The …

VEC Collaborative Task Offloading and Resource Allocation Based on Deep Reinforcement Learning Under Parking Assistance

J Xue, F Shao, T Zhang, G Tian, H Jiang - Wireless Personal …, 2024 - Springer
With the emergence of autonomous vehicles, meeting the vehicle's computing needs for
computationally intensive and latency-sensitive tasks has become a challenge. Cellular …

An RSU-crossed dependent task offloading scheme for vehicular edge computing based on deep reinforcement learning

X Bi, J Shi, B Zhang, Z Lyu… - International Journal of …, 2023 - inderscienceonline.com
Various interdependent and computationally intensive on-vehicle tasks have posed great
pressure on the computing power of vehicles. Vehicular edge computing (VEC) is …

Deep Reinforcement Learning Based on Actor-Critic for Task Offloading in Vehicle Edge Computing

B Wang, L Liu, J Wang - 2023 IEEE International Symposium …, 2023 - ieeexplore.ieee.org
With the rapid advancement of the Internet of Vehicles (IoV), IoV is facing the challenge of
providing connectivity and high-quality services for vehicles. Mobile edge computing (MEC) …

Distributed task offloading for large-scale vec systems: A multi-agent deep reinforcement learning method

Y Lu, D Han, X Wang, Q Gao - 2022 14th International …, 2022 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is a promising technology to meet the ultra-low delay
requirements of many emerging Internet of Vehicles (IoV) resource-intensive tasks. Based …

Deep reinforcement learning based offloading decision algorithm for vehicular edge computing

X Hu, Y Huang - PeerJ Computer Science, 2022 - peerj.com
Task offloading decision is one of the core technologies of vehicular edge computing.
Efficient offloading decision can not only meet the requirements of complex vehicle tasks in …

A Deep-Reinforcement-Learning-Based Computation Offloading With Mobile Vehicles in Vehicular Edge Computing

J Lin, S Huang, H Zhang, X Yang… - IEEE Internet of Things …, 2023 - ieeexplore.ieee.org
Vehicular edge networks involve edge servers that are close to mobile devices to provide
extra computation resource to complete the computation tasks of mobile devices with low …

Deep Reinforcement Learning Based on Parked Vehicles-Assisted for Task Offloading in Vehicle Edge Computing

B Wang, L Liu, J Wang - 2023 International Wireless …, 2023 - ieeexplore.ieee.org
Vehicles may produce a lot of data that is timesensitive and computationally intensive due to
the quick development of on-board applications. Due to the limitation of vehicle computing …

[HTML][HTML] DRL-assisted delay optimized task offloading in automotive-industry 5.0 based VECNs

MA Mirza, J Yu, S Raza, M Krichen, M Ahmed… - Journal of King Saud …, 2023 - Elsevier
The rapid growth of Automotive-Industry 5.0 and its emergence with beyond fifth-generation
(B5G) communications, is making vehicular edge computing networks (VECNs) increasingly …

Federated deep reinforcement learning for task offloading and resource allocation in mobile edge computing-assisted vehicular networks

X Zhao, Y Wu, T Zhao, F Wang, M Li - Journal of Network and Computer …, 2024 - Elsevier
Mobile edge computing (MEC) enables computation intensive applications in the Internet of
Vehicles (IoV) to no longer be limited by device resources. However, the lack of an effective …