Node selection method based on Markov location prediction in vehicle networking

The traditional vehicle network data acquisition is limited by coverage and real-time performance, while the data acquisition method based on Mobile Crowd-Sensing has strong mobility and perception. However, the current research on the data acquisition of the vehicle network Mobile Crowd-Sensing is insufficient. There is no reasonable node selection mechanism, so designing a reasonable service node selection method is a hot topic in current research. In this paper, a reasonable service node selection method is proposed. The Markov location prediction method of Gaussian analysis is used to estimate the probability of each vehicle node to the target area. Then we use the genetic algorithm to select the service node, and finally the optimal service node is output. Experimental results show that this method is feasible.