Cloud-Based Cognitive Radio Adhoc Vehicular Network Architecture: A Next-Generation Smart City

Abstract

In architecting a smart city, the designers and architects need to incorporate efficient mechanisms to manage movement of people, especially in urban areas. Such mechanisms usually depend heavily on the availability of efficient information and communication technologies. This paper proposes a Cloud-based cognitive radio adhoc vehicular network (CRAVENET), which plays a significant role in facilitating the development and implementation of various services in the operation of smart cities. CRAVENET also facilitates efficiently spectrum utilization by offering opportunities for cooperation among wireless service providers. CRAVENET architecture enables information collected by individual vehicles to be shared between them so as to facilitate the offering of multiple services needed for the operation of smart cities. We validate the proposed architecture using OMNeT++ and estimate its utility for information sharing and decision making. The simulation focuses on information available and/or gathered along a road trip like road conditions, trip data, traffic and climatic conditions, the status of vehicles' health, accessible vehicle service stations, and business centers.