Vehicular Networking: A Survey and Tutorial on Requirements, Architectures, Challenges, Standards and Solutions

By G. Karagiannis, Onur Altintas, Eylem Ekici, G. Heijenk, B. Jarupan, Kenneth Lin, Timothy R. Weil. IEEE Communications Surveys and Tutorials, 2011

1,528 citations recorded by the source corpus.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/fdf72e14c2c22960cdd0c3d1109b71b725fc0d0b

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In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

Routing in Internet of Vehicles: A Review (2015, background): “, cooperative downloading [113] and infotainment applications [114], [115].”
Pseudonym Schemes in Vehicular Networks: A Survey (2015, background): “[2] complete the previous survey by describing the basic characteristics and requirements of vehicular ad hoc networks (VANET), and the standardization efforts and ITS projects current in 2011.”
Artificial Neural Networks-Based Machine Learning for Wireless Networks: A Tutorial (2017, background): “ collision detection. Vehicular Networks: Vehicular networks leverage wireless connectivity to provide on-road services such as forwarding safety messages as well as trafﬁc and congestion monitoring [227]. In vehicular networks, some vehicles can be selected to act as temporary content providers for”
Resource Allocation for D2D-Enabled Vehicular Communications (2017, background): “11p, also known as wireless access for vehicular environments (WAVE), is the de facto standard for vehicular communications based on ad hoc networks [2], [7].”
Toward Social Internet of Vehicles: Concept, Architecture, and Applications (2015, methodology): “B. SIoV SYSTEM ARCHITECTURE In this section, we describe the overall architecture of the proposed system (Figure 1) which consists of six components: tNoteMessage, On Board Unit (OBU), Road Side Unit (RSU), Home Base Unit (HBU), tNote Cloud, and User Interface.”
Heterogeneous Vehicular Networking: A Survey on Architecture, Challenges, and Solutions (2015, background): “However, there are still several challenges for using DSRC in V2V communications [5], [8], [43].”
Cooperative Adaptive Cruise Control in Real Traffic Situations (2014, background): “Research projects have been conducted throug hout the world to define the requirements for an appropriate vehicular communication system and its possible applicati ons [2].”
Connected Vehicles: Solutions and Challenges (2014, background): “An overview of the current and past major related projects in the USA, Japan, and Europe can be seen in [57].”
A survey on vehicular cloud computing (2014, positive): ““Secure Relative Location Determination in Vehicular Network” (SRLD) is one of the localization methods proposed by Tang et al. (Tang et al. , 2006) to determine the correct locations of a set of connected vehicles by using the locations of surrounding vehicles.”
A Survey on Acquisition, Tracking, and Pointing Mechanisms for Mobile Free-Space Optical Communications (2018, background): “11p [10] and long term evolution (LTE) [11], [12], have”
How Can Edge Computing Benefit From Software-Defined Networking: A Survey, Use Cases, and Future Directions (2017, background): “There are important constraints in vehicular communication that directly affect the performance of the overall architecture such as high speeds, unreliable wireless connection and highly dynamic topology [124].”
Physical Layer Security for Next Generation Wireless Networks: Theories, Technologies, and Challenges (2017, background): “(1) In high speed mobile networks, such as vehicular ad hoc networks (VANETs) and high speed railway communication systems [222]–[224], the channel coefficients will change quickly.”
IoT Privacy and Security Challenges for Smart Home Environments (2016, background): “The next stage of development will be communication between vehicles, and between vehicles and infrastructure [13].”
A Survey on Resource Allocation for 5G Heterogeneous Networks: Current Research, Future Trends, and Challenges (2020, background): “5G integrates diverse technologies, such as vehicular networking [3], deviceto-device (D2D) communications [4], machine-to-machine”
A Comparative Survey of VANET Clustering Techniques (2017, background): “Several detailed studies of these issues have previously been presented in [16] and [17].”
Machine Learning for Wireless Networks with Artificial Intelligence: A Tutorial on Neural Networks (2017, background): “• Vehicular Networks: Vehicular networks leverage wireless connectivity to provide on-road services such as forwarding safety messages as well as traffic and congestion monitoring [227].”