Abstract
The Internet of Vehicles (IoV) is an emerging research framework, with network and graph theories as two of the major fields. Researchers in these topics use a variety of tools and approaches to simulate and perform experimentation on their proposed methodologies. A comprehensive study to facilitate the selection of such simulation tools is lacking from the literature. In this work, we provide a systematic review of the different simulation platforms. More precisely, the contributions of this paper are fourfold: firstly, we propose a two-tier hierarchical taxonomy based on the trends in the literature; secondly, we investigate the strengths and limitations of different simulation platforms; and thirdly, we take a network theoretic approach to identify the patterns in IoV research. To this end, we create a network of the publications and populate the edges among them. Community detection is performed using Louvian and Clauset-Newman-Moore algorithms. To the best of our knowledge, this is a novel approach to reviewing the literature which provides a more in-depth analysis of the trends in the literature. Finally, we review the common datasets for IoV experimentation.
Highlights
The Internet of Vehicles (IoV) is an inter-network of autonomous and connected vehicles that interact with one another using an ensemble of wireless protocols
Based on a systematic review of the literature, we propose a taxonomy of papers that incorporate network and graph theories in addition to classifying them based on the particular IoV application
We review the papers with keywords ‘network theory,’ ‘graph theory,’ ‘IoV,’ ‘Intelligent Transportation Systems,’ and ‘VANET’ and identified the most relevant ones
Summary
The Internet of Vehicles (IoV) is an inter-network of autonomous and connected vehicles that interact with one another using an ensemble of wireless protocols. This paper provides an evaluation of both simulation tools and experimentation methods across different applications of network and graph theories in the IoV. Based on a systematic review of the literature, we propose a taxonomy of papers that incorporate network and graph theories in addition to classifying them based on the particular IoV application. These serve as a starting point for researchers intending to research the IoV; and these provide insights on the research gaps and how to properly conduct meaningful and effective experimentation. We evaluate the strengths and limitations of current simulations and examine the trends in using specific simulators for particular research applications. We apply complex network theory to our findings and identify the different communities based on the keywords, which demonstrates the research trends. We conduct a survey on the most commonly used datasets for IoV research
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