Internet of Vehicles (IoV) is the evolution of VANET (Vehicular Ad-hoc Networks) and Intelligent Transportation Systems (ITS) focused on reaping the benefits of data generated by various sensors within these networks. The IoV is further empowered by a centralized cloud and distributed fog-based infrastructure. The myriad amounts of data generated by the vehicles and the environment have the potential to enable diverse services. These services can benefit from both variety and velocity of the generated data. This paper focuses on the data at the edge nodes to enable fog-based services that can be consumed by various IoV safety and non-safety applications. The paper emphasizes the challenges involved in offering the context-aware services in a IoV environment. In order to overcome these challenges, the paper proposes a data analytics framework for fog infrastructures at the fog layer of traditional IoV architecture that offers context-aware real time, near real-time and batch services at the edge of a network. Finally, the appropriateness of the proposed framework is verified through different use cases in IoV environment.

Big Data, Cloud computing, Computer architecture, Context-Aware Computing, Context-aware services, Data Driven Intelligence, Edge computing, Fog Computing, Internet of Vehicles, Safety
IEEE Access
School of Information Technology

Iqbal, R. (Razi), Butt, T.A. (Talal Ashraf), Shafiq, M.O, Talib, M.W.A. (Manar Wasif Abu), & Umar, T. (Tariq). (2018). Context-Aware Data-Driven Intelligent Framework for Fog Infrastructures in Internet of Vehicles. IEEE Access. doi:10.1109/ACCESS.2018.2874592