Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges

Aliyu, Ahmed, Abdullah, Abdul, Kaiwartya, Omprakash, Cao, Yue, Usman, Mohammed, Kumar, Sushil, Lobiyal, Daya and Ram, S. R. (2018) Cloud Computing in VANETs: Architecture, Taxonomy, and Challenges. IETE Technical Review, 35 (5). pp. 523-547. ISSN 0256-4602

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Official URL: http://doi.org/10.1080/02564602.2017.1342572

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, 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, co-ordination, artificial intelligence and smart application layers. Three network component 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 are 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 literature on CC-V.

Item Type: Article
Uncontrolled Keywords: Cloud Computing, Vehicular Ad-hoc Networks, Architecture, Taxonomy, Vehicular Cloud, Vehicle using Cloud
Subjects: G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Yue Cao
Date Deposited: 21 Sep 2017 15:19
Last Modified: 01 Aug 2021 13:05
URI: http://nrl.northumbria.ac.uk/id/eprint/31209

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