Linkage Selection Strategy Based on Attractor Profit Prediction in Heterogeneous Vehicle Network

Abstract

With the continuous development of wireless network technology, heterogeneous wireless networks with multiple network fusions and overlapping coverage have been formed. In the process of vehicles passing through different types of networks with different coverage areas at high speed, there are frequent and inefficient network switching behaviors. Aiming at this situation, a linkage selection strategy based on attractor profit prediction is proposed in a heterogeneous vehicle network. By analyzing the correlation between the wireless network transmission rate and the vehicle position, the location of the attractor update was found to reduce the transmission loss caused by network switching delay. Considering the vehicle speed and the access time of the base station, the transmission amount that the vehicle network can provide is calculated, the attractor is updated, and the network selection is made according to the state of the attractor. Compared with multi-attribute decision making, the linkage selection strategy based on attractor profit prediction can effectively improve the transmission volume of the Internet of vehicles. Through the simulation analysis, the transmission volume of the Internet of vehicles network increases by 14.07%.