Multi-objective task offloading for highly dynamic heterogeneous Vehicular Edge Computing: An efficient reinforcement learning approach-Reference-Cited by-同舟云学术

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Multi-objective task offloading for highly dynamic heterogeneous Vehicular Edge Computing: An efficient reinforcement learning approach

Published:2024-09 Issue: Volume:225 Page:27-43
ISSN:0140-3664
Container-title:Computer Communications
language:en
Short-container-title:Computer Communications

Author:

Huang ZhiDong,Wu XiaoFei,Dong ShouBin^ORCID

Publisher

Elsevier BV

Reference48 articles.

1. A deep-reinforcement-learning-based computation offloading with mobile vehicles in vehicular edge computing;Lin;IEEE Internet Things J.,2023

2. Reinforcement learning methods for computation offloading: A systematic review;Zabihi;ACM Comput. Surv.,2023

3. Dynamic edge computation offloading for internet of vehicles with deep reinforcement learning;Yao;IEEE Trans. Intell. Transp. Syst.,2023

4. Task offloading method of edge computing in internet of vehicles based on deep reinforcement learning;Zhang;Cluster Comput.,2022

5. Task offloading scheme combining deep reinforcement learning and convolutional neural networks for vehicle trajectory prediction in smart cities;Zeng;Comput. Commun.,2023

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