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 largescale 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, the authors propose a hybrid simulation approach that can significantly reduce the number of scheduled events by making use of statistical models. Basically, they 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 the authors only need to simulate via discrete event-based simulation the actual application they are interested in (e.g., a data dissemination protocol). The authors 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.
Enabling efficient and accurate large-scale simulations of VANETs for vehicular traffic management
2007
10 Seiten, 15 Bilder, 18 Quellen
Aufsatz (Konferenz)
Englisch
Spatial random modeling of vehicular traffic in VANETs
IEEE | 2017
|Vehicular Network Enabling Large-Scale and Real-Time Immersive Participation
Springer Verlag | 2014
|