  Vehicular users are emerging as a prime market for targeted advertisement,
where advertisements (ads) are sent from network points of access to vehicles,
and displayed to passengers only if they are relevant to them. In this study,
we take the viewpoint of a broker managing the advertisement system, and
getting paid every time a relevant ad is displayed to an interested user. The
broker selects the ads to broadcast at each point of access so as to maximize
its revenue. In this context, we observe that choosing the ads that best fit
the users' interest could actually hurt the broker's revenue. In light of this
conflict, we present Volfied, an algorithm allowing for conflict-free,
near-optimal ad selection with very low computational complexity. Our
performance evaluation, carried out through real-world vehicular traces, shows
that Volfied increases the broker revenue by up to 70% with provably low
computational complexity, compared to state-of-the-art alternatives.
