Computation offloading strategy based on deep reinforcement learning for connected and autonomous vehicle in vehicular edge computing
B Lin, K Lin, C Lin, Y Lu, Z Huang, X Chen - Journal of Cloud Computing, 2021 - Springer
Abstract Connected and Automated Vehicle (CAV) is a transformative technology that has
great potential to improve urban traffic and driving safety. Electric Vehicle (EV) is becoming …
great potential to improve urban traffic and driving safety. Electric Vehicle (EV) is becoming …
A deep reinforcement learning based computation offloading with mobile vehicles in vehicular edge computing
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 …
extra computation resource to complete the computation tasks of mobile devices with low …
Task offloading for vehicular edge computing with edge-cloud cooperation
Vehicular edge computing (VEC) is emerging as a novel computing paradigm to meet low
latency demands for computation-intensive vehicular applications. However, most existing …
latency demands for computation-intensive vehicular applications. However, most existing …
Deep reinforcement learning-based computation offloading in vehicular edge computing
Inspired by mobile edge computing (MEC), vehicular edge computing (VEC) enables
vehicle terminals to support resource-hungry on-vehicle applications with significantly lower …
vehicle terminals to support resource-hungry on-vehicle applications with significantly lower …
Deep reinforcement learning for shared offloading strategy in vehicle edge computing
X Peng, Z Han, W Xie, C Yu, P Zhu, J Xiao… - IEEE Systems …, 2022 - ieeexplore.ieee.org
Vehicular edge computing (VEC) effectively reduces the computing load of vehicles by
offloading computing tasks from vehicle terminals to edge servers. However, offloading of …
offloading computing tasks from vehicle terminals to edge servers. However, offloading of …
Multiagent deep reinforcement learning for vehicular computation offloading in IoT
X Zhu, Y Luo, A Liu, MZA Bhuiyan… - IEEE Internet of Things …, 2020 - ieeexplore.ieee.org
The development of the Internet of Things (IoT) and intelligent vehicles brings a comfortable
environment for users. Various emerging vehicular applications using artificial intelligence …
environment for users. Various emerging vehicular applications using artificial intelligence …
Deep reinforcement learning-based computation offloading in vehicular networks
L Geng, H Zhao, H Liu, Y Wang… - 2021 8th IEEE …, 2021 - ieeexplore.ieee.org
With the rapid development of 5G communications and the Internet of Things (IoT), vehicular
networks have enriched people's lives with abundant applications. Since most of such …
networks have enriched people's lives with abundant applications. Since most of such …
A distributed dependency-aware offloading scheme for vehicular edge computing based on policy gradient
H Liu, H Zhao, L Geng, Y Wang… - 2021 8th IEEE …, 2021 - ieeexplore.ieee.org
The proliferation of smart transportation has significantly promoted explosive growth of the
Internet of Vehicles (IoV). Especially, with the rapid development of the 5-th generation …
Internet of Vehicles (IoV). Especially, with the rapid development of the 5-th generation …
Advanced deep learning-based computational offloading for multilevel vehicular edge-cloud computing networks
The promise of low latency connectivity and efficient bandwidth utilization has driven the
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …
recent shift from vehicular cloud computing (VCC) towards vehicular edge computing (VEC) …
Deep-reinforcement-learning-based offloading scheduling for vehicular edge computing
Vehicular edge computing (VEC) is a new computing paradigm that has great potential to
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …