Advanced Resource Management in Fog Computing Vehicular Networks using Hybrid PSO and Min-Max Strategies

The integration of IoV and FC abates congestion on roads, increased transport effectiveness, and privacy in vehicular networks. NOMA technology enhances the spectral efficiency and access capacity of network: However, the existing IoV infrastructure is failing to cop up with the modern need for intelligent transportation due to its low scalability and high data burden. An Allocation Framework for Hybrid Resources in NOMA-based Fog Computing Vehicular Networks (FCVR) Employing Particle Swarm Optimization (PSO) and Min-Max Techniques. This involves simulations of NOMA-based Fog Computing Vehicular Network and resource allocation through Min-Max and PSO techniques. The approach to be taken will be to evaluate ergodic capacities. This invention provides a robust solution, thus, can be customized in a dynamical vehicular environment and lays down the future groundwork for research on how to enhance fog computing applications over VANETs.