Enhancing vehicular edge computing system through cooperative computation offloading
Author:
Funder
Fundamental Research Funds for the Central Universities
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Software
Link
https://link.springer.com/content/pdf/10.1007/s10586-022-03803-z.pdf
Reference44 articles.
1. Qiao, G., Leng, S., Maharjan, S., Zhang, Y., Ansari, N.: Deep reinforcement learning for cooperative content caching in vehicular edge computing and networks. IEEE Internet Things J. 7(1), 247–257 (2020)
2. Feng, J., Liu, Z., Wu, C., Ji, Y.: Mobile edge computing for the internet of vehicles: offloading framework and job scheduling. IEEE Veh. Technol. Mag. 14(1), 28–36 (2019)
3. Zhao, J., Ni, S., Yang, L., Zhang, Z., Gong, Y., You, X.: Multiband cooperation for 5G HetNets: a promising network paradigm. IEEE Veh. Technol. Mag. 14(4), 85–93 (2019). https://doi.org/10.1109/MVT.2019.2935793
4. Abbas, N., Zhang, Y., Taherkordi, A., Skeie, T.: Mobile edge computing: a survey. IEEE Internet Things J. 5(1), 450–465 (2018). https://doi.org/10.1109/JIOT.2017.2750180
5. Jian, C., Bao, L., Zhang, M.: A high-efficiency learning model for virtual machine placement in mobile edge computing. Cluster Comput 25, 3051–3066 (2022). https://doi.org/10.1007/s10586-022-03550-1
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