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Published in:
A Markov Approximation Algorithm for Computation Offloading and Resource Scheduling in Mobile Edge Computing Read chapter Read first chapter

2019 | OriginalPaper | Chapter

Edge Computing for Intelligent Transportation System: A Review

Authors : Qian Li, Pan Chen, Rui Wang

Published in: Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health

Publisher: Springer Singapore

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Abstract

To meet the demands of vehicular applications, edge computing as a promising paradigm where cloud computing services are extended to the edge of networks can enable ITS applications. In this paper, we first briefly introduced the edge computing. Then we reviewed recent advancements in edge computing based intelligent transportation systems. Finally, we presented the challenges and the future research direction. Our study provides insights for this novel promising paradigm, as well as research topics about edge computing in intelligent transportation system.

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previous chapter Improve the Efficiency of Maintenance for Optical Communication Network: The Multi-factor Risk Analysis via Edge Computing
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Literature
1.
Sahni, Y., Cao, J., Zhang, S., Yang, L.: Edge mesh: a new paradigm to enable distributed intelligence in internet of things. IEEE Access 5, 16441–16458 (2017)CrossRef
2.
Ning, Z., Wang, X., Huang, J.: Mobile edge computing-enabled 5G vehicular networks: toward the integration of communication and computing. IEEE Veh. Technol. Mag. 14(1), 54–61 (2019)CrossRef
3.
Swarnamugi, M., Chinnaiyan, R.: IoT hybrid computing model for intelligent transportation system (ITS). In: 2nd International Conference on Computing Methodologies and Communication (ICCMC), Erode, pp. 802–806 (2018)
4.
Liu, K., Xu, X., Chen, M., Liu, B., Wu, L., Lee, V.C.S.: A hierarchical architecture for the future internet of vehicles. IEEE Commun. Mag. 57(7), 41–47 (2019)CrossRef
5.
Peng, H., Ye, Q., Shen, X.: Spectrum management for multi-access edge computing in autonomous vehicular networks. IEEE Trans. Intell. Transp. Syst. Early Access, 1–12 (2019)
6.
Zhou, Z., Feng, J., Chang, Z., Shen, X.: Energy-efficient edge computing service provisioning for vehicular networks: a consensus ADMM approach. IEEE Trans. Veh. Technol. 68(5), 5087–5099 (2019)CrossRef
7.
Hui, Y., Su, Z., Luan, T.H., Cai, J.: Content in motion: an edge computing based relay scheme for content dissemination in urban vehicular networks. IEEE Trans. Intell. Transp. Syst. 20(8), 3115–3128 (2019)CrossRef
8.
Yu, C., Lin, B., Guo, P., Zhang, W., Li, S., He, R.: Deployment and dimensioning of fog computing-based internet of vehicle infrastructure for autonomous driving. IEEE Internet of Things J. 6(1), 149–160 (2019)CrossRef
9.
Qi, Q., et al.: Knowledge-driven service offloading decision for vehicular edge computing: a deep reinforcement learning approach. IEEE Trans. Veh. Technol. 68(5), 4192–4203 (2019)CrossRef
10.
Tan, L.T., Hu, R.Q.: Mobility-aware edge caching and computing in vehicle networks: a deep reinforcement learning. IEEE Trans. Veh. Technol. 67(11), 10190–10203 (2018)CrossRef
11.
Aissioui, A., Ksentini, A., Gueroui, A.M., Taleb, T.: On enabling 5G automotive systems using follow me edge-cloud concept. IEEE Trans. Veh. Technol. 67(6), 5302–5316 (2018)CrossRef
12.
Ge, X., Li, Z., Li, S.: 5G software defined vehicular networks. IEEE Commun. Mag. 55(7), 87–93 (2017)CrossRef
13.
Cui, J., Wei, L., Zhang, J., Xu, Y., Zhong, H.: An efficient message-authentication scheme based on edge computing for vehicular ad hoc networks. IEEE Trans. Intell. Transp. Syst. 20(5), 1621–1632 (2019)CrossRef
14.
Kang, J., Yu, R., Huang, X., Zhang, Y.: Privacy-preserved pseudonym scheme for fog computing supported internet of vehicles. IEEE Trans. Intell. Transp. Syst. 19(8), 2627–2637 (2018)CrossRef
15.
Guo, F., et al.: Detecting vehicle anomaly in the edge via sensor consistency and frequency characteristic. IEEE Trans. Veh. Technol. 68(6), 5618–5628 (2019)CrossRef
16.
Sun, Y., et al.: Adaptive learning-based task offloading for vehicular edge computing systems. IEEE Trans. Veh. Technol. 68(4), 3061–3074 (2019)CrossRef
17.
Zhou, Z., Liu, P., Feng, J., Zhang, Y., Mumtaz, S., Rodriguez, J.: Computation resource allocation and task assignment optimization in vehicular fog computing: a contract-matching approach. IEEE Trans. Veh. Technol. 68(4), 3113–3125 (2019)CrossRef
18.
Liu, S., Liu, L., Tang, J., Yu, B., Wang, Y., Shi, W.: Edge computing for autonomous driving: opportunities and challenges. Proc. IEEE 107, 1697–1716 (2019)CrossRef
19.
Khattak, H.A., Islam, S.U., Din, I.U., Guizani, M.: Integrating fog computing with VANETs: a consumer perspective. IEEE Commun. Stand. Mag. 3(1), 19–25 (2019)CrossRef
Metadata
Title
Edge Computing for Intelligent Transportation System: A Review
Authors
Qian Li
Pan Chen
Rui Wang
Copyright Year
2019
Publisher
Springer Singapore
Book
Cyberspace Data and Intelligence, and Cyber-Living, Syndrome, and Health

Print ISBN: 978-981-15-1924-6

Electronic ISBN: 978-981-15-1925-3

Copyright Year: 2019

DOI
https://doi.org/10.1007/978-981-15-1925-3_10

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