• Journal of Digital Convergence
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• v.12 no.6
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• pp.265-270
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• 2014

The working-day movement model, which implemented in the ONE simulator, supports the environments similar to the real life by using the transportation. However, there is no taxi movement model in the working-day movement model. So, we implemented a taxi movement model in the ONE simulator as the previous work. It is changed significantly for the simulation results of routing protocols in the ONE simulator. In this paper, we analyze the performance evaluation of the DTN routing protocol such as an epidemic routing protocol using our taxi movement model in the ONE simulator.

• Journal of Digital Convergence
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• v.13 no.1
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• pp.237-241
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• 2015

The ONE simulator has been used the tool for the DTN routing protocols. A movement model on DTN characteristic importantly affects to the simulation results of routing protocols. Especially, the WDM model provides the real similar situation such as commuting using vehicles, movements to a meeting point in office hours, activities after work, and etc. Our previous work proposed a taxi movement model in the WDM model. However, there is a difference between the real situations and the proposed model in finding a passenger. In this paper, we proposed an advanced taxi movement model with a taxi driver's locality and visibility range in order to configurate the real similar situation. And we analyze the difference between the previous model and the proposed model.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.7
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• pp.3018-3040
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• 2018

The mobility model is one of the most important factors that impacts the evaluation of any transportation vehicular networking protocols via simulations. However, to obtain a realistic mobility model in the dynamic urban environment is a very challenging task. Several studies extract mobility models from large-scale real data sets (mostly taxi GPS data) in recent years, but they do not consider the statuses of taxi, which is an important factor affected taxi's mobility. In this paper, we discover three simple observations related to the taxi statuses via mining of real taxi trajectories: (1) the behavior of taxi will be influenced by the statuses, (2) the macroscopic movement is related with different geographic features in corresponding status, and (3) the taxi load/drop events are varied with time period. Based on these three observations, a novel taxi mobility model (T-START) is proposed with respect to taxi statuses, geographic region and time period. The simulation results illustrate that proposed mobility model has a good approximation with reality in trajectory samples and distribution of nodes in four typical time periods.