Dynamic Task Offloading and Resource Allocation for Vehicular Edge Computing Networks Based on Deep Reinforcement Learning

Xia Yang; Haixia Zhang; Jie Tian; Dongfeng Yuan

doi:10.1109/tvt.2025.3612473

ScienceGate Book Chapters

JOURNAL ARTICLE

Dynamic Task Offloading and Resource Allocation for Vehicular Edge Computing Networks Based on Deep Reinforcement Learning

Xia Yang Haixia Zhang Jie Tian Dongfeng Yuan

Year: 2025 Journal: IEEE Transactions on Vehicular Technology Pages: 1-10 Publisher: Institute of Electrical and Electronics Engineers

DOI: 10.1109/tvt.2025.3612473

Get Full-Text PDF Get Analytical Report

Keywords:

Metrics

Cited By

0.00

FWCI (Field Weighted Citation Impact)

Refs

0.42

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Topics

IoT and Edge/Fog Computing

Physical Sciences → Computer Science → Computer Networks and Communications

Age of Information Optimization

Physical Sciences → Computer Science → Computer Networks and Communications

Privacy-Preserving Technologies in Data

Physical Sciences → Computer Science → Artificial Intelligence

Dynamic Task Offloading and Resource Allocation for Vehicular Edge Computing Networks Based on Deep Reinforcement Learning

Metrics

Topics

Related Documents

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

Task offloading in vehicular edge computing networks via deep reinforcement learning

Task Offloading and Resource Allocation for ICVs in Vehicular Edge Computing Networks Based on Hybrid Hierarchical Deep Reinforcement Learning

Multi-agent deep reinforcement learning-based partial offloading and resource allocation in vehicular edge computing networks

Adaptive Task Offloading in Vehicular Edge Computing Networks Based on Deep Reinforcement Learning