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Enabling Collaborative Edge Computing for Software Defined Vehicular Networks
Abstract
Edge computing has great potential to address the challenges in mobile vehicular networks by transferring partial storage and computing functions to network edges. However, it is still a challenge to efficiently utilize heterogeneous edge computing architectures and deploy large-scale IoV systems. In this article, we focus on the collaborations among different edge computing anchors and propose a novel collaborative vehicular edge computing framework, called CVEC. Specifically, CVEC can support more scalable vehicular services and applications by both horizontal and vertical collaborations. Furthermore, we discuss the architecture, principle, mechanisms, special cases, and potential technical enablers to support the CVEC. Finally, we present some research challenges as well as future research directions.
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Cited by
Bhushan, B., Khamparia, A., Sagayam, K. M., Sharma, S. K., Ahad, M. A., & Debnath, N. C. (2020) · Sustainable Cities and Society · doi:10.1016/j.scs.2020.102360 · Cited by 353
Blockchain for smart communities: applications, challenges and opportunities
Aggarwal, S., Chaudhary, R., Aujla, G. S., Kumar, N., Choo, K.-K. R., & Zomaya, A. Y. (2019) · Journal of Network and Computer Applications · doi:10.1016/j.jnca.2019.06.018 · Cited by 344
A computation offloading method over big data for IoT-enabled cloud-edge computing
Xu, X., Liu, Q., Luo, Y., Peng, K., Zhang, X., Meng, S., & Qi, L. (2019) · Future Generation Computer Systems · doi:10.1016/j.future.2018.12.055 · Cited by 336
Emerging Technologies for 5G-IoV Networks: Applications, Trends and Opportunities
Duan, W., Gu, J., Wen, M., Zhang, G., Ji, Y., & Mumtaz, S. (2020) · IEEE Network · doi:10.1109/mnet.001.1900659 · Cited by 299
Applications of Game Theory in Vehicular Networks: A Survey
Sun, Z., Liu, Y., Wang, J., Li, G., Anil, C., Li, K., Guo, X., Sun, G., Tian, D., & Cao, D. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2021.3108466 · Cited by 68
Metadata
- Authors
- Wang, K., Yin, H., Quan, W., & Min, G.
- Venue
- IEEE Network
- Published
- 2018-09
- Volume
- 32
- Issue
- 5
- Pages
- 112-117
- ISSN
- 0890-8044 (ISSN-L)
- 1558-156X
- OpenAlex
- W2790588927
- Cited by
- 212
- References
- 0
- FWCI
- 23.34
- Type
- journal article
- Language
- en
- Open access
- closed
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- Wang, K., Yin, H., Quan, W., & Min, G. (2018). Enabling Collaborative Edge Computing for Software Defined Vehicular Networks. IEEE Network. https://doi.org/10.1109/mnet.2018.1700364
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