  Cooperative inter-vehicular applications rely on the exchange of broadcast
single-hop status messages among vehicles, called beacons. The aggregated load
on the wireless channel due to periodic beacons can prevent the transmission of
other types of messages, what is called channel congestion due to beaconing
activity. In this paper we approach the problem of controlling the beaconing
rate on each vehicle by modeling it as a Network Utility Maximization (NUM)
problem. This allows us to formally apply the notion of fairness of a beaconing
rate allocation in vehicular networks and to control the trade-off between
efficiency and fairness. The NUM methodology provides a rigorous framework to
design a broad family of simple and decentralized algorithms, with proved
convergence guarantees to a fair allocation solution. In this context, we focus
exclusively in beaconing rate control and propose the Fair Adaptive Beaconing
Rate for Intervehicular Communications (FABRIC) algorithm, which uses a
particular scaled gradient projection algorithm to solve the dual of the NUM
problem. The desired fairness notion in the allocation can be established with
an algorithm parameter. Simulation results validate our approach and show that
FABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.
