Content accessibility preference approach for improving service optimality in internet of vehicles

Abstract The Internet of Vehicles (IoV) is an application of Internet of Things that provides a solution for traffic and safety management in technology-dependent cities. The most competent resource for IoV functionalities is the distributed Information System (IS). Services outsourced from the IS are not sustained over a long period of time, owing to unpredictable network dynamics and localization errors. Considering that the IS is the backbone for the IoV, this manuscript proposes a low-delay information accessing technique for improving the service optimality of vehicle-assisted smart applications. The vehicles for gaining access to information by selecting optimal gateways exploit the benefits of epidemic spread routing (ESR). The greedy behavior of ESR is confined by designing a content accessibility preference (CAP) model that facilitates precise vehicle selection. This selection relies on the information relevance, granted by the neighboring vehicles to deliver improved service optimality. The reliability of the vehicle with regard to the relevance and information retrieval time is verified by the cooperative on-demand relationship between the service requesting on-board unit and the roadside unit. Both gateway selection and neighbor vehicle selection are assimilated for providing better service via distributed information access and relevant information retrieval. The performance of the proposed CAP model is evaluated using the following metrics: throughput, access delay, vehicle service ratio, and optimality ratio. The results show the proficiency of the proposed CAP method.