Abstract
Decision-making is of critical significance in Internet-of-Vehicles (IoV), where vehicles need to quickly make decisions in real-time when sharing or transferring the information. In addition, it is necessary to identify the significant factors of an entity while measuring its legitimacy or to record the real-time data generated by it. Traditional automated schemes in IoV are confronted by the issues related to real-time processing and the manner they respond, such as traffic congestion information, fastest route selection, and road accidental information. The exchange of accurate information among vehicles is critical, but the decision-making for IoV has still not been fully investigated in the literature. Further, the involvement of malicious devices in the network may disgrace the network performance by consuming network resources. In this paper, we propose a hybrid decision-making scheme in vehicular informatics for data transferring and processing through VIKOR and analytic hierarchy process (AHP) methods. The proposed model is scrutinized and verified rigorously through several sensing and decision-making metrics against a conventional solution. The simulation results depict that the proposed model leads to 93 percent competence in terms of decision-making, identification of legitimate sensors, and data alteration process when sharing the information through various sensors in IoV.