The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System
Abstract
Fog computing has been merged with Internet of Vehicle (IoV) systems to provide computational resources for end users, by which low latency can be guaranteed. In this paper, we put forward a feasible solution that enables offloading for real-time traffic management in fog-based IoV systems, aiming to minimize the average response time for events reported by vehicles. First, we construct a distributed city-wide traffic management system, in which vehicles close to road side units can be utilized as fog nodes. Then, we model parked and moving vehicle-based fog nodes according to a queueing theory, and draw the conclusion that moving vehicle-based fog nodes can be modeled as an $M/M/1$ queue. An approximate approach is developed to solve the offloading optimization problem by decomposing it into two subproblems and scheduling traffic flows among different fog nodes. Performance analyses based on a real-world taxi-trajectory datasets are conducted to illustrate the superiority of our method.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Internet of Things in industries: A survey
Xu, L. D., He, W., & Li, S. (2014) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2014.2300753 · Cited by 5,172
Theoretical Improvements in Algorithmic Efficiency for Network Flow Problems
Edmonds, J., & Karp, R. M. (1972) · Journal of the ACM · doi:10.1145/321694.321699 · Cited by 2,528
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
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×
“For instance, the information about a traffic jam may be only valid for half an hour, and can merely draw attentions of vehicles that are moving toward the area where the traffic jam occurs [10].”
BackgroundEnergy-Latency Tradeoff for Energy-Aware Offloading in Mobile Edge Computing Networks
Zhang, J., Hu, X., Ning, Z., Ngai, E. C.-H., Zhou, L., Wei, J., Cheng, J., & Hu, B. (2018) · IEEE Internet of Things Journal · doi:10.1109/jiot.2017.2786343 · Cited by 577
Self-citationGreen Internet of Things for Smart World
Zhu, C., Leung, V. C. M., Shu, L., & Ngai, E. C.-H. (2015) · IEEE Access · doi:10.1109/access.2015.2497312 · Cited by 494
Vehicular Social Networks: Enabling Smart Mobility
Ning, Z., Xia, F., Ullah, N., Kong, X., & Hu, X. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1600263 · Cited by 343
Self-citationA 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-citationZhang, W., Zhang, Z., & Chao, H.-C. (2017) · IEEE Communications Magazine · doi:10.1109/mcom.2017.1700208 · Cited by 235
Cited by
Deep Learning for Smart Industry: Efficient Manufacture Inspection System With Fog Computing
Li, L., Ota, K., & Dong, M. (2018) · IEEE Transactions on Industrial Informatics · doi:10.1109/tii.2018.2842821 · Cited by 466
Resource management approaches in fog computing: a comprehensive review
Ghobaei-Arani, M., Souri, A., & Rahmanian, A. A. (2020) · Journal of Grid Computing · doi:10.1007/s10723-019-09491-1 · Cited by 365
Reliable Computation Offloading for Edge-Computing-Enabled Software-Defined IoV
Hou, X., Ren, Z., Wang, J., Cheng, W., Ren, Y., Chen, K.-C., & Zhang, H. (2020) · IEEE Internet of Things Journal · doi:10.1109/jiot.2020.2982292 · Cited by 334
Deep Reinforcement Learning for Vehicular Edge Computing: An Intelligent Offloading System
Ning, Z., Dong, P., Wang, X., Rodrigues, J. J. P. C., & Xia, F. (2019) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3317572 · Cited by 292
Self-citationHuang, X., Li, P., Yu, R., Wu, Y., Xie, K., & Xie, S. (2021) · IEEE Transactions on Vehicular Technology · doi:10.1109/tvt.2021.3098170 · Cited by 115
Metadata
- Authors
- Wang, X., Ning, Z., & Wang, L.
- Venue
- IEEE Transactions on Industrial Informatics
- Published
- 2018-10
- Volume
- 14
- Issue
- 10
- Pages
- 4568-4578
- ISSN
- 1551-3203 (ISSN-L)
- 1941-0050
- OpenAlex
- W2789986657
- Cited by
- 398
- References
- 22
- FWCI
- 37.97
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System. https://app.cochat.ai/papers/10.1109/tii.2018.2816590
- The paper
- Wang, X., Ning, Z., & Wang, L. (2018). Offloading in Internet of Vehicles: A Fog-Enabled Real-Time Traffic Management System. IEEE Transactions on Industrial Informatics. https://doi.org/10.1109/tii.2018.2816590
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
