Computing Paradigms in Emerging Vehicular Environments: A Review Lion Silva, Naercio Magaia, Breno Sousa, Anna Kobusińska, António Casimiro, Constandinos X. Mavromoustakis, Senior Member, IEEE, George Mastorakis, and Victor Hugo C. de Albuquerque, Senior Member, IEEE Abstract—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. Index Terms— Computing paradigm, cloud, edge, fog, internet of vehicle (IoV), vehicular networks.   I. Introduction I N this work, we introduce fundamental concepts of computing paradigms and their use in emerging vehicular environments and later analyze those that may be more promising in the near future. Usually, these paradigms have much in common in terms of the need for proper functioning, particularly in such environments. Specifically, an efficient, fast, and integrated network is necessary for different forms of wireless connectivity. We chose to adopt a logical instead of physical perspective regarding the paradigm layers in question. Regarding vehicular networks, we recall the need to provide safer traffic, and therefore protect human life, whether in large cities, on highways, or in rural areas. Intelligent transportation systems (ITS) is a concept that covers both connected vehicle networks, and any other means that involves the cooperative, efficient, intelligent, safe, and economical transportation of people and goods with the construction of an infrastructure that is integrated with the means of transportation in question. Hence, there is a flow of data that, when transformed into information, allows drivers and managers to make the best decisions in perspective and real-time. A vehicular ad-hoc network (VANET) is a specific type of mobile ad-hoc network (MANET) where network nodes (i.e., vehicles) self-organize themselves to provide some simple but essential set of services. The internet of vehicle (IoV) is a novel vehicular environment with more powerful infrastructural elements (i.e., 4G/5G and Wi-Fi-enable OBUs, Access Points to the Internet, connection to the cloud, among others). In conjunction, these elements bring a novel set of applications and services not only fulfilling ITS but also commercial ones requirements. VANET still has its value as it has been in stable development for 30 years. Its distributed and simple architecture is well suited to safety applications between nearby vehicles and pedestrians. Furthermore, it can provide simple, informative, and local services to the driver, such as nearby gas stations or traffic warnings in nearer electronic road signs. Vehicular computing paradigms are an essential evolution of cloud and edge computing in vehicular environments. Using the newest communication technologies, and specific protocol techniques, these two paradigms provide a more robust and efficient network, in which cars can act such as cloud servers whenever the situation permits (i.e., in parking 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. L. Silva, N. Magaia, B. Sousa, and A. Casimiro are with LASIGE, Department of Computer Science, Faculty of Sciences, University of Lisbon, Lisbon 1749-016, Portugal (e-mail: lsilva@lasige.di.fc.ul.pt; ndmagaia@ ciencias.ulisboa.pt; bfmelo@fc.ul.pt; accosta@ciencias.ulisboa.pt). A. Kobusińska is with the Laboratory of Computing Science, Poznań University of Technology, Poznan 60-965, Poland (e-mail: Anna.Kobusinska@ cs.put.poznan.pl). C. X. Mavromoustakis is with the Department of Computer Science, University of Nicosia, Nicosia CY-2417, Cyprus (e-mail: mavromoustakis. c@unic.ac.cy). G. Mastorakis is with the Department of Management Science and Technology, Hellenic Mediterranean University, Agios Nikolaos 72100, Greece (e-mail: gmastorakis@hmu.gr). V. H. C. Albuquerque is with LAPISCO, Federal Institute of Education, Science and Technology of Ceará, Fortaleza 60750-740, and also with ARMTEC Tecnologia em Robótica, Fortaleza 60150000, Brazil (e-mail: victor.albuquerque@ieee.org). Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/JAS.2021.1003862 IEEE/CAA JOURNAL OF AUTOMATICA SINICA, VOL. 8, NO. 3, MARCH 2021 491