We investigate the broadcast problem in suburban and highway inter-vehicular networks, aiming at providing a definitive comparison of two antipodean broadcast algorithm classes: the first one makes use of some instantaneous information locally available at the vehicles (such as vehicle position and speed), while the second one relies on long-term knowledge gained through a beaconing procedure. Using a realistic microscopic model to represent the vehicular traffic flow, we investigate the performance of the above broadcast algorithm classes by simulation, considering different classes of network services (e.g., Critical, Normal, and Low-priority). In order to explore a very large algorithmic design space, we devise a convex hull framework that allows us to effectively compare and compactly present the boundaries of the solution space for each algorithm class. By the use of such framework, we show that the beaconless performance encompasses a wider spectrum with respect to the beaconed one, with lower complexity and overhead.
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