A simulation framework for supporting vehicular knowledge networks

Vehicular Knowledge Networking (VKN) is a paradigm where vehicles exchange knowledge instead of data. Named Data Networking (NDN) is a resilient architecture for sharing data between vehicles without information about the hosting vehicle. NDN might not be adapted for sharing knowledge, as the peculiar complexity of knowledge requires knowledge-driven NDN functions as well as a specific simulation environment enabling joint knowledge perception, inference and reasoning. In this paper, we present an open-source cosimulation framework connecting NDN, traffic, dynamic control and perception simulators for knowledge perception & inference, and with an AI-as-a-Service (AIaaS) platform for knowledge reasoning. This paper notably describes new interfaces and functions between the NDN daemon and the AIaaS micro-services for handling interest naming, caching and forwarding between knowledge producers and consumers. We demonstrate the benefit of the proposed framework and knowledge-specific extensions through an AI-driven vehicular intersection management.