The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Toward cloud-based vehicular networks with efficient resource management
Open accessAbstract
In the era of the Internet of Things, all components in intelligent transportation systems will be connected to improve transport safety, relieve traffic congestion, reduce air pollution, and enhance the comfort of driving. The vision of all vehicles connected poses a significant challenge to the collection and storage of large amounts of traffic-related data. In this article, we propose to integrate cloud computing into vehicular networks such that the vehicles can share computation resources, storage resources, and bandwidth resources. The proposed architecture includes a vehicular cloud, a roadside cloud, and a central cloud. Then we study cloud resource allocation and virtual machine migration for effective resource management in this cloud-based vehicular network. A game-theoretical approach is presented to optimally allocate cloud resources. Virtual machine migration due to vehicle mobility is solved based on a resource reservation scheme.
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
The case for vm-based cloudlets in mobile computing
Satyanarayanan, M., Bahl, P., Caceres, R., & Davies, N. (2009) · IEEE Pervasive Computing · doi:10.1109/mprv.2009.82 · Cited by 3,660
Cited by
Taleb, T., Samdanis, K., Mada, B., Flinck, H., Dutta, S., & Sabella, D. (2017) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2017.2705720 · Cited by 1,775
A Comprehensive Survey of RAN Architectures Toward 5G Mobile Communication System
Habibi, M. A., Nasimi, M., Han, B., & Schotten, H. D. (2019) · IEEE Access · doi:10.1109/access.2019.2919657 · Cited by 312
Masip-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
Recent advances in connected and automated vehicles
Elliott, D., Keen, W., & Miao, L. (2019) · Journal of Traffic and Transportation Engineering (English Edition) · doi:10.1016/j.jtte.2018.09.005 · Cited by 253
Spinelli, F., & Mancuso, V. (2021) · IEEE Communications Surveys & Tutorials · doi:10.1109/comst.2020.3037674 · Cited by 253
Metadata
- Authors
- Yu, R., Zhang, Y., Gjessing, S., Xia, W., & Yang, K.
- Venue
- IEEE Network
- Published
- 2013-09
- Volume
- 27
- Issue
- 5
- Pages
- 48-55
- ISSN
- 0890-8044 (ISSN-L)
- OpenAlex
- W2114574164
- Cited by
- 415
- References
- 1
- FWCI
- 22.97
- Type
- journal article
- Language
- en
- Open access
- green
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: Toward cloud-based vehicular networks with efficient resource management. https://app.cochat.ai/papers/10.1109/mnet.2013.6616115
- The paper
- Yu, R., Zhang, Y., Gjessing, S., Xia, W., & Yang, K. (2013). Toward cloud-based vehicular networks with efficient resource management. IEEE Network. https://doi.org/10.1109/mnet.2013.6616115
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.
