On An Intelligent Task Offloading Model to Jointly Optimize Latency and Energy for Electric Connected Vehicles
With modern Electric Connected Vehicles (ECVs) becoming more intelligent and
entertaining, the Multi-access Edge Computing (MEC) servers deployed near the Road Side …
entertaining, the Multi-access Edge Computing (MEC) servers deployed near the Road Side …
Joint Optimization of Energy and Delay in Task Offloading Process of Electric Connected Vehicles
The rapid development of 5G and battery has enabled the electricity-driven intelligent
connected vehicles to become the focus of current automobile industry. With automobiles …
connected vehicles to become the focus of current automobile industry. With automobiles …
Deep Reinforcement Learning-Based Adaptive Computation Offloading and Power Allocation in Vehicular Edge Computing Networks
B Qiu, Y Wang, H Xiao, Z Zhang - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
As a novel paradigm, Vehicular Edge Computing (VEC) can effectively support computation-
intensive or delay-sensitive applications in the Internet of Vehicles era. Computation …
intensive or delay-sensitive applications in the Internet of Vehicles era. Computation …
Latency-energy tradeoff in connected autonomous vehicles: A deep reinforcement learning scheme
Vehicle Edge Computing (VEC)-assisted computational offloading brings cloud computing
closer to user equipment (UEs) at the edge of the access network by delivering various …
closer to user equipment (UEs) at the edge of the access network by delivering various …
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 …
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 …
[HTML][HTML] 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 …
Deep reinforcement learning-guided task reverse offloading in vehicular edge computing
The rapid development of Vehicular Edge Computing (VEC) provides great support for
Collaborative Vehicle Infrastructure System (CVIS) and promotes the safety of autonomous …
Collaborative Vehicle Infrastructure System (CVIS) and promotes the safety of autonomous …
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 …
application businesses have recently emerged, such as the Telematics business. The …
Deep Reinforcement Learning Based Distributed Computation Offloading in Vehicular Edge Computing Networks
L Geng, H Zhao, J Wang, A Kaushik… - IEEE Internet of …, 2023 - ieeexplore.ieee.org
Vehicular edge computing has emerged as a promising paradigm by offloading computation-
intensive latency-sensitive tasks to mobile-edge computing (MEC) servers. However, it is …
intensive latency-sensitive tasks to mobile-edge computing (MEC) servers. However, it is …