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Aliyu, A., Abdullah, A.H., Kaiwartya, O. 
ORCID: 0000-0001-9669-8244, Cao, Y., Usman, M.J., Kumar, S., Lobiyal, D.K. and Raw, R.S.,
2018.
Cloud computing in VANETs: architecture, taxonomy, and challenges.
IETE Technical Review, 35 (5), pp. 523-547.
ISSN 0256-4602
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Abstract
Cloud computing in VANETs (CC-V) has been investigated into two major themes of research including vehicular cloud computing (VCC) and vehicle using cloud (VuC). VCC is the realization of autonomous cloud among vehicles to share their abundant resources. VuC is the efficient usage of conventional cloud by on-road vehicles via a reliable Internet connection. Recently, a number of advancements have been made to address the issues and challenges in VCC and VuC. This paper qualitatively reviews CC-V with the emphasis on layered architecture, network component, taxonomy, and future challenges. Specifically, a four-layered architecture for CC-V is proposed including perception, coordination, artificial intelligence and smart application layers. Three network components of CC-V, namely, vehicle, connection, and computation are explored with their cooperative roles. A taxonomy for CC-V is presented considering major themes of research in the area including design of architecture, data dissemination, security, and applications. Related literature on each theme is critically investigated with comparative assessment of recent advances. Finally, some open research challenges are identified as future issues. The challenges are the outcome of the critical and qualitative assessment of the literature on CC-V.
| Item Type: | Journal article | ||||||
|---|---|---|---|---|---|---|---|
| Publication Title: | IETE Technical Review | ||||||
| Creators: | Aliyu, A., Abdullah, A.H., Kaiwartya, O., Cao, Y., Usman, M.J., Kumar, S., Lobiyal, D.K. and Raw, R.S. | ||||||
| Publisher: | Taylor & Francis | ||||||
| Date: | 3 September 2018 | ||||||
| Volume: | 35 | ||||||
| Number: | 5 | ||||||
| ISSN: | 0256-4602 | ||||||
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| Rights: | Copyright © 2018 Informa UK Limited. This is an Accepted Manuscript of an article published by Taylor & Francis in IETE Technical Review on 23 Aug 2017, available at: http://www.tandfonline.com/10.1080/02564602.2017.1342572. | ||||||
| Divisions: | Schools > School of Science and Technology | ||||||
| Record created by: | Linda Sullivan | ||||||
| Date Added: | 10 Jan 2023 11:33 | ||||||
| Last Modified: | 10 Jan 2023 11:35 | ||||||
| URI: | https://irep.ntu.ac.uk/id/eprint/47783 |
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