Research on task offloading optimization strategies for vehicular networks based on game theory and deep reinforcement learning
L Wang, W Zhou, H Xu, L Li, L Cai, X Zhou - Frontiers in Physics, 2023 - frontiersin.org
With the continuous development of the 6G mobile network, computing-intensive and delay-
sensitive onboard applications generate task data traffic more frequently. Particularly, when …
sensitive onboard applications generate task data traffic more frequently. Particularly, when …
A dependency-aware offloading algorithm based on deep reinforcement learning for vehicular networks
Y Wang, H Zhao, H Liu, L Geng - … International Conference on …, 2021 - ieeexplore.ieee.org
Recent years have witnessed the explosive growth of ubiquitous vehicles with extremely
intelligent systems, which results in large amounts of data generated. Most of these vehicle …
intelligent systems, which results in large amounts of data generated. Most of these vehicle …
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 …
requirements of many emerging Internet of Vehicles (IoV) resource-intensive tasks. Based …
DRL-Based Hybrid Task Offloading and Resource Allocation in Vehicular Networks
Z Liu, Z Jia, X Pang - Electronics, 2023 - mdpi.com
With the explosion of delay-sensitive and computation-intensive vehicular applications,
traditional cloud computing has encountered enormous challenges. Vehicular edge …
traditional cloud computing has encountered enormous challenges. Vehicular edge …
Task offloading and resource allocation in vehicular networks: A Lyapunov-based deep reinforcement learning approach
AS Kumar, L Zhao, X Fernando - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) has gained popularity due to its ability to enhance
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …
vehicular networks. VEC servers located at Roadside Units (RSUs) allow low-power …
A Hybrid Deep Reinforcement Learning Approach for Jointly Optimizing Offloading and Resource Management in Vehicular Networks
CL Chen, B Bhargava, V Aggarwal… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Satisfying the quality of service of data-intensive autonomous driving applications has
become challenging. In this work, we propose a novel methodology that optimizes …
become challenging. In this work, we propose a novel methodology that optimizes …
Deadline-aware task offloading in vehicular networks using deep reinforcement learning
MK Farimani, S Karimian-Aliabadi… - Expert Systems with …, 2024 - Elsevier
Smart vehicles have a rising demand for computation resources, and recently vehicular
edge computing has been recognized as an effective solution. Edge servers deployed in …
edge computing has been recognized as an effective solution. Edge servers deployed in …
Deep reinforcement learning-based joint optimization model for vehicular task offloading and resource allocation
ZY Li, ZX Zhang - Peer-to-Peer Networking and Applications, 2024 - Springer
With the rapid advancement of Internet of vehicles and autonomous driving technology,
there is a growing need for increased computing power in vehicle operations. However, the …
there is a growing need for increased computing power in vehicle operations. However, the …
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 …
DRL-based resource allocation for computation offloading in IoV networks
Due to the dynamic nature of a vehicular fog computing environment, efficient real-time
resource allocation in an Internet of Vehicles (IoV) network without affecting the quality of …
resource allocation in an Internet of Vehicles (IoV) network without affecting the quality of …
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