The DOI matches its Crossref record; 15 of the 15 references it cites were found in a registry or an index.
Vehicular Fog Computing: Enabling Real-Time Traffic Management for Smart Cities
Abstract
Fog computing extends the facility of cloud computing from the center to edge networks. Although fog computing has the advantages of location awareness and low latency, the rising requirements of ubiquitous connectivity and ultra-low latency challenge real-time traffic management for smart cities. As an integration of fog computing and vehicular networks, vehicular fog computing (VFC) is promising to achieve real-time and location-aware network responses. Since the concept and use case of VFC are in the initial phase, this article first constructs a three-layer VFC model to enable distributed traffic management in order to minimize the response time of citywide events collected and reported by vehicles. Furthermore, the VFC-enabled offloading scheme is formulated as an optimization problem by leveraging moving and parked vehicles as fog nodes. A real-world taxi-trajectory-based performance analysis validates our model. Finally, some research challenges and open issues toward VFC-enabled traffic management are summarized and highlighted.
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Cites
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Kleinrock, L. (1975) · Cited by 1,972
Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures
Hou, X., Li, Y., Chen, M., Wu, D., Jin, D., & Chen, S. (2016) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2016.2532863 · Cited by 930
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Butterworth, R. W., & Kleinrock, L. (1976) · Journal of the American Statistical Association · doi:10.2307/2285630 · Cited by 713
Zhang, K., Mao, Y., Leng, S., He, Y., & ZHANG, Y. (2017) · IEEE Vehicular Technology Magazine · doi:10.1109/mvt.2017.2668838 · Cited by 701
Securing Fog Computing for Internet of Things Applications: Challenges and Solutions
Ni, J., Zhang, K., Lin, X., & Shen, X. (2018) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2762345 · Cited by 659 · cited 1×
“The security and privacy requirements of VFC-enabled crowdsensing are discussed in [12], including the unique infrastructure and various promising applications (e.”
BackgroundAn effective key management scheme for heterogeneous sensor networks
Du, X., Xiao, Y., Guizani, M., & Chen, H.-H. (2007) · Ad Hoc Networks · doi:10.1016/j.adhoc.2006.05.012 · Cited by 471
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Vehicular Fog Computing: Architecture, Use Case, and Security and Forensic Challenges
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“IEEE Wireless Communications • February 2019 88 system was presented as a use case [1].”
BackgroundMethodA Cooperative Quality-Aware Service Access System for Social Internet of Vehicles
Ning, Z., Hu, X., Chen, Z., Zhou, M., Hu, B., Cheng, J., & Obaidat, M. S. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2764259 · Cited by 287
Self-citationMasip-Bruin, X., Marín-Tordera, E., Tashakor, G., Jukan, A., & Ren, G.-J. (2016) · IEEE Wireless Communications · doi:10.1109/mwc.2016.7721750 · Cited by 267
Cited by
Smart cities—a structured literature review
Gracias, J. S., Parnell, G. S., Specking, E., Pohl, E. A., & Buchanan, R. (2023) · Smart Cities · doi:10.3390/smartcities6040080 · Cited by 476
Deep Reinforcement Learning for Autonomous Internet of Things: Model, Applications and Challenges
Lei, L., Tan, Y., Zheng, K., Liu, S., Zhang, K., & Shen, X. (2020) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.2988367 · Cited by 298
Ning, Z., Zhang, K., Wang, X., Obaidat, M. S., Guo, L., Hu, X., Hu, B., Guo, Y., Sadoun, B., & Kwok, R. Y. K. (2021) · IEEE Transactions on Intelligent Transportation Systems · doi:10.1109/tits.2020.2970276 · Cited by 268
Self-citationQuality of Service Optimization in an IoT-Driven Intelligent Transportation System
Sodhro, A. H., Obaidat, M. S., Abbasi, Q. H., Pace, P., Pirbhulal, S., Yasar, A.-U.-H., Fortino, G., Imran, M. A., & Qaraqe, M. (2019) · IEEE Wireless Communications · doi:10.1109/mwc.001.1900085 · Cited by 153
A Hierarchical Architecture for the Future Internet of Vehicles
Liu, K., Xu, X., Chen, M., Liu, B., Wu, L., & Lee, V. C. S. (2019) · IEEE Communications Magazine · doi:10.1109/mcom.2019.1800772 · Cited by 133
Metadata
- Authors
- Ning, Z., Huang, J., & Wang, X.
- Venue
- IEEE Wireless Communications
- Published
- 2019-02
- Volume
- 26
- Issue
- 1
- Pages
- 87-93
- ISSN
- 1536-1284 (ISSN-L)
- 1558-0687
- OpenAlex
- W2914289538
- Cited by
- 425
- References
- 15
- FWCI
- 36.49
- Type
- journal article
- Language
- en
- Open access
- closed
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