TY - JOUR
T1 - Computing Paradigms in Emerging Vehicular Environments
T2 - A Review
AU - Silva, Lion
AU - Magaia, Naercio
AU - Sousa, Breno
AU - Kobusinska, Anna
AU - Casimiro, Antonio
AU - Mavromoustakis, Constandinos X.
AU - Mastorakis, George
AU - De Albuquerque, Victor Hugo C.
N1 - Funding Information:
Manuscript received July 23, 2020; revised September 29, 2020; accepted November 17, 2020. This work was supported by FCT through the LASIGE Research Unit (UIDB/00408/2020, UIDP/00408/2020) and the Brazilian National Council for Research and Development (CNPq) (#304315/2017-6, #430274/2018-1). Recommended by Associate Editor MengChu Zhou. (Corresponding author: Naercio Magaia.) Citation: L. Silva, N. Magaia, B. Sousa, A. Kobusińska, A. Casimiro, C. X. Mavromoustakis, G. Mastorakis, and V. H. C. Albuquerque, “Computing paradigms in emerging vehicular environments: A review,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 3, pp. 491–511, Mar. 2021.
Publisher Copyright:
© 2014 Chinese Association of Automation.
Copyright:
Copyright 2021 Elsevier B.V., All rights reserved.
PY - 2021/3
Y1 - 2021/3
N2 - Determining how to structure vehicular network environments can be done in various ways. Here, we highlight vehicle networks' evolution from vehicular ad-hoc networks (VANET) to the internet of vehicles (IoVs), listing their benefits and limitations. We also highlight the reasons in adopting wireless technologies, in particular, IEEE 802.11p and 5G vehicle-to-everything, as well as the use of paradigms able to store and analyze a vast amount of data to produce intelligence and their applications in vehicular environments. We also correlate the use of each of these paradigms with the desire to meet existing intelligent transportation systems' requirements. The presentation of each paradigm is given from a historical and logical standpoint. In particular, vehicular fog computing improves on the deficiences of vehicular cloud computing, so both are not exclusive from the application point of view. We also emphasize some security issues that are linked to the characteristics of these paradigms and vehicular networks, showing that they complement each other and share problems and limitations. As these networks still have many opportunities to grow in both concept and application, we finally discuss concepts and technologies that we believe are beneficial. Throughout this work, we emphasize the crucial role of these concepts for the well-being of humanity.
AB - Determining how to structure vehicular network environments can be done in various ways. Here, we highlight vehicle networks' evolution from vehicular ad-hoc networks (VANET) to the internet of vehicles (IoVs), listing their benefits and limitations. We also highlight the reasons in adopting wireless technologies, in particular, IEEE 802.11p and 5G vehicle-to-everything, as well as the use of paradigms able to store and analyze a vast amount of data to produce intelligence and their applications in vehicular environments. We also correlate the use of each of these paradigms with the desire to meet existing intelligent transportation systems' requirements. The presentation of each paradigm is given from a historical and logical standpoint. In particular, vehicular fog computing improves on the deficiences of vehicular cloud computing, so both are not exclusive from the application point of view. We also emphasize some security issues that are linked to the characteristics of these paradigms and vehicular networks, showing that they complement each other and share problems and limitations. As these networks still have many opportunities to grow in both concept and application, we finally discuss concepts and technologies that we believe are beneficial. Throughout this work, we emphasize the crucial role of these concepts for the well-being of humanity.
KW - cloud
KW - Computing paradigm
KW - edge
KW - fog
KW - internet of vehicle (IoV)
KW - vehicular networks
UR - http://www.scopus.com/inward/record.url?scp=85099787399&partnerID=8YFLogxK
U2 - 10.1109/JAS.2021.1003862
DO - 10.1109/JAS.2021.1003862
M3 - Article
AN - SCOPUS:85099787399
SN - 2329-9266
VL - 8
SP - 491
EP - 511
JO - IEEE/CAA Journal of Automatica Sinica
JF - IEEE/CAA Journal of Automatica Sinica
IS - 3
M1 - 9346073
ER -