Data Gathering in Urban Vehicular Network Based on Daily Movement Patterns

With the rapid development of vehicular, communication and sensing technologies, intelligent transportation system(ITS) and vehicular network are widely used to improve the driving experience in the city. A key procedure of many applications in vehicular network is data gathering, a universal process to collect sensed data from sparse-distributed vehicles for further operations to provide services. However, state-of-the-art routing or data gathering methods paid attentions only to the short-term movement features but ignore the strong regularity of long-term daily movement patterns of people. In this paper, we proposed a general framework of data gathering in vehicular network based on the regularity of daily movements of vehicles. Simulation experiment results show that our method could archive a satisfied data delivery rate in a low amount of data transmission overhead in urban scenario.