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Madrid Highways Dataset | Link available after paper acceptance

(Our paper presenting the dataset generation and analysis is currently under review. We will publicly release the dataset upon acceptance of the paper. We thank you for your understanding. )

There is a growing need for vehicular mobility datasets that can be employed in the simulative evaluation of protocols and architectures designed for upcoming vehicular networks. Such datasets should be realistic, publicly available, and heterogeneous. In [1], we contribute to the ongoing effort to define such mobility scenarios, by introducing this novel set of traces for vehicular network simulation. These traces are derived from high-detail real-world traffic counts and describe the road traffic on two highways around Madrid, Spain, at several hours of different working days. In the paper [1] we provide a thorough discussion of the real-world data underlying our study, and of the synthetic trace generation process. The road traffic dataset is formed by 16 different mobility traces, resulting from the 2 roads, 4 dates and 2 time intervals. Due to the filesize of the dataset, the length of the road segment is 10km and the time granularity is 1 second. The format of the files is:                 <time> <nodeID> <x> <y> <speed>

  • [1] Vehicular Networks on Madrid Highways Marco Gramaglia, Oscar Trullols-Cruces, Diala Naboulsi, Marco Fiore, Maria Calderon

Large-scale VANET simulator | Download

The computational complexity of the simulations that reproduce the movement and network traffic of several thousands of vehicles at a time, prevent the use of a traditional network simulator, such as ns-2. Instead, we developed a dedicated simulator, which employs the mobility extracted from the Mobility traces and considers a simple disc model for signal propagation. It avoids the detailed reproduction of the entire network stack at each node, while it allows to tune several dissemination propagation model parameters. (More details in a paper [1]) The simulator allows to choose which node(or nodes) starts the dissemination and when it is initiated. Nodes move as defined by the mobility trace, and contact opportunities and contact durations are obtained using a disc model signal propagation. The dissemination spreads constrained to the dissemination propagation parameters. At any time, it is possible to obtain global statistics (number of nodes, number of infected nodes, car trips ended, car trips ended infected, ...), as well as the list of nodes present in the scenario with their position, and infected status. This simulator has been used to analyze a scenario of 100x100 Km^2 with a 3.683 Km road layout for a submitted paper. We hope to publish more details soon.

  • [1] Understanding, Modeling and Taming Mobile Malware Epidemics in a Large-scale Vehicular Network Oscar Trullols-Cruces, Marco Fiore, Jose M. Barcelo-Ordinas, IEEE WoWMoM 2013, 4-7 June, Madrid

VANET chunk scheduling simulator | Download

Traditional network simulators (e.g. ns-2) requirements are too high to reproduce the mobility and network traffic of several thousands of vehicles during a long time period. To deal with this kind of scenarios we developed this VANET chunk-level scheduling simulator. It replaces the traditional packet-level simulation with a more scalable chunk-level one, avoiding the detailed reproduction of the entire network stack at each node. It implements the cooperative download techniques presented in [1] and all the extensions, the oracle-scheduler, and the extensive output data gathering used in [2]. We used them with ETH Zurich Realistic Vehicular Traces, translating them to the following format to feed our simulator:                 <time> <nodeID> <x> <y> <speed> More info about how to compile and use it can be found in the 'readme.txt' included in the package.

  • [1] Cooperative download in urban vehicular networks Marco Fiore, Jose M. Barcelo-Ordinas, IEEE MASS 2009, Macau, China, October 2009

  • [2] Cooperative download in vehicular environments Oscar Trullols-Cruces, Marco Fiore, Jose M. Barcelo-Ordinas, Accepted for IEEE Transactions on Mobile Computing (TMC)