POST: Exploiting Dynamic Sociality for Mobile Advertising in Vehicular Networks

Jun Qin, Hongzi Zhu, Yanmin Zhu, Li Lu, Guangtao Xue and Minglu Li

in Proceedings of IEEE INFOCOM 2014, Toronto, Canada.

Mobile advertising in vehicular networks is of great interest with which timely information can be fast spread into the network. Given a limited budget for hiring seed vehicles, how to achieve the maximum advertising coverage within a given period of time is NP-hard. In this paper, we propose an innovative scheme, POST, for mobile advertising in vehicular networks. The POST design is based on two key observations we have found by analyzing three large-scale vehicle traces. First, vehicles demonstrate dynamic sociality in the network; second, such vehicular sociality has strong temporal correlations. With the knowledge, POST uses Markov chains to infer future vehicular sociality and adopts one greedy heuristic to select the most “centric” vehicles as seeds for mobile advertising. Extensive trace-driven simulation results show that POST can greatly improve the coverage and the intensity of advertising.

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