Big Data Processing and Analysis in Internet of Vehicles: Architecture, Taxonomy, and Open Research Challenges

The extensive progression in the Internet of Vehicles (IoV) and the exponential upsurge in data consumption reflect the importance of big data in IoV. In general, big data has gained a significant attraction in academia and industry to provide valuable business intelligence and evidence-based decisions. This has been a key enabler for the advancement of the Internet of Vehicles (IoV) in which big data can be leveraged for efficient processing and valuable decisions. Moreover, data acquired from connected vehicles, traffic monitoring, social media feeds, and, crowd-sourcing can strengthen urban development and management. The purpose of this study is to synthesize a systematic review of all related research articles from January 2014 to September 2020 in well-alleged venues. We have rigorously surveyed the research papers to understand potential opportunities, methodologies, and challenges of using big data in IoV. This review shows that big data can play a key role in providing sound and valuable predictions and also provide a comprehensive analysis of several methods, tools, and techniques for the use of big data in IoV. Apart from reviewing the state-of-the-art studies of using big data in IoV, a taxonomy of the said also has been proposed. Furthermore, the article outlined and discussed several key challenges in IoV with notable recommendations and open research dimensions for using big data in IoV.