Title: Route forecasting-based authentication scheme using A* algorithm in vehicular communication network

Authors: Vartika Agarwal; Sachin Sharma; Gagan Bansal

Addresses: Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India ' Department of Computer Science and Engineering, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India ' Department of Mechanical Engineering, Indian Institute of Technology (BHU), Varanasi, Uttar Pradesh, India

Abstract: Researchers have developed several authentication techniques for route predictions based on user requirements. These techniques estimate the shortest path and available resources in vehicular communication networks. In the current research, the existing authentication techniques for vehicular communication are compared and their inadequacies are identified. Then, new authentication technique based on route forecasting are presented for vehicular communication networks, with the service provider anticipating alternate routes for customers if the current routes have more network traffic congestion. By presenting the most efficient route, the suggested model allows users to maximise their time efficiency. Using A* algorithm, VCN agent seeks path with less network traffic congestion. This algorithm determines the shortest path between a source and a destination. Users are provided with several options by the service provider. User accepts the finest option that meets their needs. This method allows the service provider to deliver at least 15 routes within three seconds. This strategy is beneficial when a significant number of vehicles are stuck in traffic and consumers require network resources to utilise their time effectively.

Keywords: vehicular communication network; route prediction-based authentication scheme; network traffic congestion; network traffic index.

DOI: 10.1504/IJVICS.2023.131602

International Journal of Vehicle Information and Communication Systems, 2023 Vol.8 No.1/2, pp.16 - 32

Received: 22 Nov 2022
Accepted: 06 Jan 2023
Published online: 20 Jun 2023 *