Abstract
The appearance of the Internet of Vehicles enables comfort driving experiences and content- rich multimedia services for in-vehicle users. The vehicular network provides specific scenario- centric content delivery services involving data of vehicle status, user behaviors, and environmental features. In this article, we focus on vehicular content delivery from a big data perspective. After a comprehensive review of state-of-the-art works, we elaborate the potential value of big data in vehicular information and content services by introducing several typical application scenarios. According to the data characteristics, we classify the vehicular data into three categories, that is, location-centric, user-centric, and vehicle-centric, and then illustrate an implementation of big data collection and analysis. A real-world big data application in social-based vehicular networks is presented, and simulation results show that the big-data-enabled content delivery strategy can obtain a performance gain of user satisfaction with the delivered contents compared to the case without consideration of social big data. Finally, we conclude the article with several future research topics.
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