Data gathering in urban vehicular network based on daily movement patterns
Zhijie Lin, Yongxuan Lai, Xing Hua Gao, Guilin Li, Tian Wang, Guohua Huang · 2016
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.