Abstract
Drone-assisted solutions are a demanding and popular area of research where drones can send or collect data from ground networks. The recent Internet of Vehicles (IoV) networks has suffered from congestion issue due to rapid increase and a new architecture for data transmission. Data communication in this domain is possible using vehicle nodes. Due to unique features and high mobility of nodes, dynamic topologies, unpredictable network patterns, and other obstacles degraded these networks' performance and leads to disconnection, delay, and packet dropping issues. Security is another significant concern especially in drones and vehicle nodes where malicious entry exists to disturb the network traffic. In this paper, we propose a Trust and Priority-based Drone Assisted Internet of Vehicles (TPDA-IoV) solution for data routing among vehicle nodes and drones for IoV networks. The proposed solution is based on three modules including Drone-to-drone (D2D) and Drone-tovehicle (D2V) data communication and trust evaluation. This solution is designed especially when the IoV networks are suffered from congestion issues and the ground base station is not able to handle all communication received from vehicle nodes due to congested traffic patterns and populated urban roads and limited infrastructure setup. The messages need urgent decision services to avoid any serious issues in the network. The proposed solution provides drone-assisted resources to collect or send the data by using traffic density information received from the base station. This solution is the best option for congested networks where the channels are not able to transmit the data due to density and load on their devices. The proposed solution also covers the limited battery issues of drones by selecting the preferable energy level among drones. This solution is tested in terms of packet delivery ratio, network overhead, and end-to-end delay with state of eth art solutions. The proposed solution achieved a high performance as compared to existing solutions.