Towards Computing Quality of Experience(QoE) in Social Internet of Vehicles(SIoV)

Social Internet of Vehicles (SIoV) is a potential technology which connects vehicles in an autonomous network to improve the safety and efficiency of mobility. People are more willing to take risks and interact with others if they have reason to trust those around them. The SIoV paradigm has the potential to significantly alter the way people interact with their vehicles by disseminating timely information about road conditions and facilitating a safer driving experience. The level of communication required and the nature of the information exchanged during social interactions between vehicles, people, and infrastructure may result in distinct patterns of behavior. As the Social Internet of Vehicle continues to advance, more and more IoV applications can be created that require little to no human intervention. Measuring and evaluating the quality of such SIoV applications can be difficult in the absence of human input or feedback, but is vital to guarantee that they function as expected. The majority of existing Quality of Experience (QoE) literature focus on the human evaluation of application's quality. In contrast, we provided a mathematical approach to automatically calculate the QoE based on the many significant parameters, including Quality of Service and Quality of Interaction. The functional verification has shown the accuracy of the proposed model.