Abstract
Vehicular Ad hoc Networks (VANETs) have been viewed as a key technology that can offer drivers and passengers ease of driving, convenience, comfort and safety above all. Although VANETs have already been announced or implemented, current architectures face several technical challenges in deployment and management due to poor scalability, flexibility, connectivity and lack of intelligence. The integration of Cloud, Fog and Edge Computing in VANETs together with the use of Software Defined Networking (SDN) promise to deal with these challenges. In this paper, we present and compare two intelligent Fuzzy-based Systems for Resource Management (FSRM) in SDN-VANETs: FSRM1 and FSRM2. The proposed systems are used to make decisions on the processing layer of the applications’ data in a Cloud-Fog-Edge layered architecture and come in handy when a vehicle needs additional resources to run its application(s). The decisions are made by prioritizing the application requirements and by considering the available connections. FSRM1 decides the processing layer by considering Data Size, Time Sensitivity and Vehicle Relative Speed with Neighboring Vehicles. In addition to these parameters, FSRM2 considers the Number of Neighboring Vehicles to make its decision. We show through simulations the feasibility of our proposed systems to improve the management of the network resources.
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