The key goal of Internet of Things (IoT) has been the provision of value-added services based on the ubiquitously available smart devices that can offer diverse services by interacting with each other. However, the paradigm has evolved to its next phase, Social Internet of Things (SIoT), with the inception of an idea to empower these devices with consciousness. This cognizance enables these smart devices to socialize with each other based on shared context and mutual interests. The Social Internet of Vehicles (SIoV) applies SIoT concepts in the vehicular domain to revolutionize the existing ITS (Intelligent Transport System) by adding value to existing VANET (Vehicular Ad-hoc Network) technology. This paper presents a scalable SIoV architecture based on Restful web technology. Furthermore, this paper emphasizes the importance of web technology to meet the required interoperability to support the composition of numerous services. The paper also discusses the enabling technologies and protocols.
Internet of Vehicles (IoV) is the evolution of vehicular ad-hoc networks and intelligent transportation systems 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. This paper emphasizes the challenges involved in offering the context-aware services in an IoV environment. In order to overcome these challenges, this 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 the IoV environment.