Mobility is an important issue in the research of mobile delay-tolerant networks (DTNs). A simple grid model has been frequently used to simulate urban road networks in geographical restricted mobility models. However, by analyzing graph attributes of some urban road networks in main cities of Europe and USA, we discovered the discrepancy between real road network samples and the grid model. Based on the finding, we proposed a random graph-based road network model, called the Grid Model with Random Edges (GRE). The GRE model extends the basic grid model with new probabilistic parameters and thus has better capabilities to approximate real-world road networks. The model was validated through optimizing model parameter values using a genetic algorithm and comparing graph attributes of road networks generated by the model. It was demonstrated that the GRE model has better capability on approximating real road networks than the grid model, thus providing a better foundation for mobility modeling in mobile DTNs.
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