Enabling efficient and accurate large-scale simulations of VANETs for vehicular traffic management

To study the impact of inter-vehicle communications on (vehicular) transport efficiency, e.g., for traffic management purposes, there is a need for efficient and accurate large-scale simulations that jointly consider both, the vehicular traffic and the communication system. To overcome the scalability limitations of current discrete event-based network simulators like NS-2, we propose a hybrid simulation approach that can significantly reduce the number of scheduled events by making use of statistical models. Basically, we treat some data traffic, which is not the primary concern of the simulation study, as 'noise' (e.g., beaconing of nodes). While accurately modeling this background traffic we only need to simulate via discrete event-based simulation the actual application we are interested in (e.g., a data dissemination protocol). We outline how the characterization of the background traffic is gained, statistically validated and used. The achievable speed-up is demonstrated in a first application study where a speed funnel is built using inter-vehicle communications. In this scenario, the conservatively estimated speed-up factor is about 500 compared to a pure discrete event-based simulation.