Vehicular-based support to cutting-edge application scenarios in next-gen networks

The rapid advancements in in-vehicle computing, communication, and software enable drivers to access diverse distributed applications and services. Edge Computing and frameworks like the European Telecommunications Standards Institute (ETSI) Multi-access Edge Computing (MEC) are intended to be key in standardizing service execution at the network edge. Complementing this, Vehicular Cloud Computing (VCC) and Vehicular Edge Computing (VEC) augment edge computational capacity by harnessing vehicle computing, storage, and communication resources. Together, these technologies create a resource continuum, enabling real-time processing, low latency, and improved service quality. This dissertation presents several solutions to contribute to the creation of an innovative and powerful vehicular-based support for edge applications in next-generation networks. Hence, it extensively studies and contributes to enhancing vehicular communication reliability and advancing the vehicular computing paradigm by developing simulated/emulated platforms for application design in this domain. The key contributions of this PhD dissertation include: i) a reputation-based system to exclude misbehaving vehicles within Vehicle-to-Vehicle (V2V) communications, ii) a dataset comprising V2V messages compliant with European standards, iii) an extensive study on the usage of a Time-Sensitive Networking (TSN) middleware to improve Quality of Service (QoS) and data delivery in Vehicle-to-Everything (V2X) communications, iv) the design of a vehicular computing architecture based on recognized standards (e.g., MEC) to promote interoperability and scalability, and v) a novel simulation tool allowing researchers and engineers to design, test, and enhance distributed applications that exploit vehicular, edge, and cloud computing concepts. Furthermore, this dissertation explores MEC deployment within 5G networks using Open Radio Access Network (O-RAN) specifications, establishing a foundation for a real-world vehicular cloud computing testbed. This led to an openly accessible middleware for developing near real-time applications following O-RAN standards, essential for integrating MEC and O-RAN. All proposed solutions have been rigorously tested, demonstrating their effectiveness in advancing next-generation vehicular and edge computing.