Age of Information Modeling and Optimization for Fast Information Dissemination in Vehicular Social Networks

Autonomous vehicles (AVs) with advanced communication, computing, and control capabilities will provide not only a convenient means of transportation but also an emerging platform for real-time social communications and networking. Thereby, it is crucial to enable timely exchange of information over the dynamic cyber-physical-social system enabled by the AVs. In this paper, we consider age of information (AoI)-centric real-time information dissemination over vehicular social networks (VSNs), where the Aol captures the freshness of received data packets. We first propose a mathematical framework based on the mean-field theory (MIT) to analyze the network AoI (NAol) of VSNs, namely Aol for the AV that lastly receives the information update in the network. The proposed analytical framework considers both the social features of vehicular networks, which are characterized using the scale-free network theory, and the underlying wireless communication process to evaluate the NAol. Then, we further consider joint optimization of the information update rate at the source node and the transmit probabilities at the AVs for minimization of the average peak NAoI (PNAoI), i.e., the time average of peak values occurred in the evolution of the NAol, which is solved via a novel parametric optimization scheme. Both analytical and simulation results show that compared with several baseline schemes, the proposed scheme can exploit the scale-free feature of the VSNs to significantly lower the average PNAoI by up to 96%.

Automated summary

This paper discusses real-time information dissemination based on the Age of Information in vehicular social networks, proposing a mathematical framework and conducting joint optimization, with results showing that the new scheme can significantly reduce the average peak NAoI by up to 96%.