Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing

Mehdi Sookhak; F. Richard Yu; Ying He; Hamid Talebian; Nader Sohrabi Safa; Nan Zhao; Muhammad Khurram Khan; Neeraj Kumar

doi:10.1109/MVT.2017.2667499

Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing

Mehdi Sookhak, F. Richard Yu, Ying He, Hamid Talebian, Nader Sohrabi Safa, Nan Zhao, Muhammad Khurram Khan, Neeraj Kumar

Research output: Contribution to journal › Article › peer-review

179 Citations (Scopus)

442 Downloads (Pure)

Abstract

Fog 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.

Original language	English
Article number	7994678
Pages (from-to)	55-64
Number of pages	10
Journal	IEEE Vehicular Technology Magazine
Volume	12
Issue number	3
Early online date	27 Jul 2017
DOIs	https://doi.org/10.1109/MVT.2017.2667499
Publication status	Published - 1 Sept 2017
Externally published	Yes

Bibliographical note

© 2017 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.

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Keywords

Cloud computing
Edge computing
Computer architecture
Real-time systems
Computational modeling
Streaming media

ASJC Scopus subject areas

Automotive Engineering

Access to Document

10.1109/MVT.2017.2667499

Post-PrintAccepted author manuscript, 1.29 MB

http://wrap.warwick.ac.uk/91430/

Cite this

@article{dc3bf349bf1043529a293960c49ef09c,

title = "Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing",

abstract = "Fog 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.",

keywords = "Cloud computing, Edge computing, Computer architecture, Real-time systems, Computational modeling, Streaming media",

author = "Mehdi Sookhak and Yu, {F. Richard} and Ying He and Hamid Talebian and {Sohrabi Safa}, Nader and Nan Zhao and Khan, {Muhammad Khurram} and Neeraj Kumar",

note = "{\textcopyright} 2017 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. Copyright {\textcopyright} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. ",

year = "2017",

month = sep,

day = "1",

doi = "10.1109/MVT.2017.2667499",

language = "English",

volume = "12",

pages = "55--64",

journal = "IEEE Vehicular Technology Magazine",

issn = "1556-6072",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

number = "3",

}

TY - JOUR

T1 - Fog Vehicular Computing

T2 - Augmentation of Fog Computing Using Vehicular Cloud Computing

AU - Sookhak, Mehdi

AU - Yu, F. Richard

AU - He, Ying

AU - Talebian, Hamid

AU - Sohrabi Safa, Nader

AU - Zhao, Nan

AU - Khan, Muhammad Khurram

AU - Kumar, Neeraj

N1 - © 2017 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. Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

PY - 2017/9/1

Y1 - 2017/9/1

N2 - Fog 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.

AB - Fog 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.

KW - Cloud computing

KW - Edge computing

KW - Computer architecture

KW - Real-time systems

KW - Computational modeling

KW - Streaming media

UR - http://www.scopus.com/inward/record.url?scp=85029604996&partnerID=8YFLogxK

U2 - 10.1109/MVT.2017.2667499

DO - 10.1109/MVT.2017.2667499

M3 - Article

AN - SCOPUS:85029604996

SN - 1556-6072

VL - 12

SP - 55

EP - 64

JO - IEEE Vehicular Technology Magazine

JF - IEEE Vehicular Technology Magazine

IS - 3

M1 - 7994678

ER -

Fog Vehicular Computing: Augmentation of Fog Computing Using Vehicular Cloud Computing

Abstract

Bibliographical note

Keywords

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this