Real-Time Strategy Selection for Mobile Advertising in VANETs

Vehicular ad-hoc networks (VANETs) has recently attracted a lot of attention due to their great potentials for different applications such as collision avoidance, route finding and autonomous driving. A wide range of coverage and accessibility to the end users in VANETs make them a good target for commercial advertising. This paper addresses the problem of mobile advertising in VANETs. We consider a case where different advertisers compete for the VANET infrastructure. It is assumed that a city is partitioned into a grid of blocks and the central data center manager (CDM) sets the rental price for each block considering the geographical position and the predicted density of vehicles inside the block. The regret-based minimization method is adopted to tackle the problem in response to its dynamic nature. Regret bound of the proposed algorithm and its convergence to the best strategy are shown rigorously. Furthermore, a good potential of the proposed algorithm is revealed through simulations.