Fog vehicular computing: augmentation of fog computing using vehicular cloud computing
Yu, F Richard
Sohrabi Safa, Nader
Khan, Muhammad Khurram
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AbstractFog computing has emerged as a promising solution for accommodating the surge of mobile traffic and reducing latency, both known to be inherent problems of cloud computing. Fog services, including computation, storage, and networking, are hosted in the vicinity of end users (edge of the network), and, as a result, reliable access is provisioned to delay-sensitive mobile applications. However, in some cases, the fog computing capacity is overwhelmed by the growing number of demands from patrons, particularly during peak hours, and this can subsequently result in acute performance degradation. In this article, we address this problem by proposing a new concept called fog vehicular computing (FVC) to augment the computation and storage power of fog computing. We also design a comprehensive architecture for FVC and present a number of salient applications. The result of implementation clearly shows the effectiveness of the proposed architecture. Finally, some open issues and envisioned directions are discussed for future research in the context of FVC.
CitationSookhak, M., Yu, R., He, Y., Talebian, H., Sohrabi Safa, N., Zhao, N., Khan, M.K. and Kumar, N. (2017) Fog vehicular computing : augmentation of fog computing using vehicular cloud computing. IEEE Vehicular Technology Magazine, 12 (3). pp. 55-64. doi:10.1109/MVT.2017.2667499
JournalIEEE Vehicular Technology Magazine
Description© 20XX IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. This is an accepted manuscript of an article published by IEEE in IEEE Vehicular Technology Magazine, available online: http://dx.doi.org/10.1109/MVT.2017.2667499 The accepted version of the publication may differ from the final published version.
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