Modelling V2X CAMs in YANG for Interoperability and Management-Efficient Encoding

The miniaturisation of computing and the widespread use of wireless technology have enabled the rapid adoption of autonomous vehicle systems for safety. Consequently, it has led to a new class of cross-domain and cross-platform applications. However, these applications cannot fully exploit the infrastructure due to a lack of interoperability. Edge devices in a fog environment struggle to communicate with vehicular systems effectively as they use different communication protocols and message formats. Although common data formats such as XML and JSON exist, the stringent requirements for fast processing and compact messages preclude their practical use. Additionally, the data models underlying these formats are often incompatible with each other. First, this paper examines the translation of the ASN.1 model of Cooperative Awareness Messages (CAMs) into its semantically equivalent YANG model. Subsequently, this YANG model, which is easily understood by edge devices, enables CAMs to be serialized into the CORECONF-CBOR Template (CCT) encoding. This encoding is approximately 39.19% faster to decode than its ASN.1 counterpart (UPER). Additionally, we present a scenario to control the Internet of Vehicles using CoAP/CORECONF, which produces 84.41% smaller response size and 11.12% to 3.45% faster response times compared to HTTP/RESTCONF based methods for less than 5 users concurrently accessing the vehicle.