Efficient approaches for task offloading in point-of-interest based vehicular fog computing-Reference-Cited by-同舟云学术

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Efficient approaches for task offloading in point-of-interest based vehicular fog computing

Published:2023-10-21 Issue: Volume: Page:
ISSN:0920-8542
Container-title:The Journal of Supercomputing
language:en
Short-container-title:J Supercomput

Author:

Sun Yifei,Wu Jigang,Wu Yalan,Chen Long,Sun Weijun

Funder

National Natural Science Foundation of China

National Key Research and Development Project

Key-Area Research and Development Program of Guangdong Province

Publisher

Springer Science and Business Media LLC

Subject

Hardware and Architecture,Information Systems,Theoretical Computer Science,Software

Link

https://link.springer.com/content/pdf/10.1007/s11227-023-05698-y.pdf

Reference49 articles.

1. Liu Y, Wang S, Zhao Q, Du S, Zhou A, Ma X, Yang F (2020) Dependency-aware task scheduling in vehicular edge computing. IEEE Internet Things J 7(6):4961–4971

2. Liwang M, Dai S, Gao Z, Tang Y, Dai H (2018) A truthful reverse-auction mechanism for computation offloading in cloud-enabled vehicular network. IEEE Internet Things J 6(3):4214–4227

3. Huang J, Qian Y, Hu RQ (2019) A vehicle-assisted data offloading in mobile edge computing enabled vehicular networks. In: IEEE Global Communications Conference, pp 1–6

4. Zhang X, Zhang J, Liu Z, Cui Q, Tao X, Wang S (2020) Mdp-based task offloading for vehicular edge computing under certain and uncertain transition probabilities. IEEE Trans Veh Technol 69(3):3296–3309

5. Luo Q, Li C, Luan TH, Shi W (2020) Collaborative data scheduling for vehicular edge computing via deep reinforcement learning. IEEE Internet Things J 7(10):9637–9650

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