Cooperative inter-vehicular applications rely on the exchange of broadcastsingle-hop status messages among vehicles, called beacons. The aggregated loadon the wireless channel due to periodic beacons can prevent the transmission ofother types of messages, what is called channel congestion due to beaconingactivity. In this paper we approach the problem of controlling the beaconingrate 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 beaconingrate allocation in vehicular networks and to control the trade-off betweenefficiency and fairness. The NUM methodology provides a rigorous framework todesign a broad family of simple and decentralized algorithms, with provedconvergence guarantees to a fair allocation solution. In this context, we focusexclusively in beaconing rate control and propose the Fair Adaptive BeaconingRate for Intervehicular Communications (FABRIC) algorithm, which uses aparticular scaled gradient projection algorithm to solve the dual of the NUMproblem. The desired fairness notion in the allocation can be established withan algorithm parameter. Simulation results validate our approach and show thatFABRIC converges to fair rate allocations in multi-hop and dynamic scenarios.
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