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Key Technologies of MEC Towards 5G-Enabled Vehicular Networks

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Abstract

Mobile edge computing (MEC) can satisfy the communication requirements of ultra-high reliability and ultra-low latency in 5G-enabled vehicular networks, since it provides Internet service environment and cloud computing capability for wireless access network. In this paper, the architecture and characteristics of MEC for unmanned driving are explored. Meanwhile, the key technologies of MEC are discussed. With the assist of clustering, we propose the scheme of mobile vehicle cloud (MVC)-aided communication, and examine the network performance including computing resource allocation by MEC and link performance. The numerical results show that the network performance is improved effectively.

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Acknowledgments

This work was supported in part by the National Natural Science Foundation of China (61471031, 61661021), the State Key Laboratory of Rail Traffic Control and Safety (Contract No. RCS2017K009), the Key Technology Research and Development Program of Jiangxi Province under Grant No. 20171BBE50057, the Open Research Fund of National Mobile Communications Research Laboratory, Southeast University (No. 2017D14), Science and technology project of Jiangxi Provincial Transport Bureau (No. 2016D0037), Training Plan for the Main Subject of Academic Leaders of Jiangxi Province (No. 20172BCB22016), and Natural Science Foundation of Guangdong Province under Grant No. 2015A030313844.

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Correspondence to Junhui Zhao .

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Ma, X., Zhao, J., Gong, Y., Wang, Y. (2018). Key Technologies of MEC Towards 5G-Enabled Vehicular Networks. In: Wang, L., Qiu, T., Zhao, W. (eds) Quality, Reliability, Security and Robustness in Heterogeneous Systems. QShine 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 234. Springer, Cham. https://doi.org/10.1007/978-3-319-78078-8_16

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  • DOI: https://doi.org/10.1007/978-3-319-78078-8_16

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-78077-1

  • Online ISBN: 978-3-319-78078-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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