Probability Prediction-Based Reliable and Efficient Opportunistic Routing Algorithm for VANETs

In the vehicular ad hoc networks (VANETs), due to the high mobility of vehicles, the network parameters change frequently and the information that the sender maintains may outdate when it wants to transmit data packet to the receiver, so for improving the routing efficiency and reliability, we propose the probability prediction-based reliable and efficient opportunistic routing (PRO) algorithm for VANETs. The PRO routing algorithm can predict the variation of signal-to-interference-plus-noise ratio (SINR) and packet queue length (PQL) of the receiver. The prediction results are used to determine the utility of each relaying vehicle in the candidate set. The calculation of the vehicle's utility is the weight-based algorithm, and the weights are the variances of SINR and PQL. The relaying priority of each relaying vehicle is determined by the value of its utility. By these innovations, the PRO can achieve better routing performance (such as the packet delivery ratio, the end-to-end delay, and the network throughput) than the SRPE, ExOR (street-centric), and greedy perimeter stateless routing algorithms.