Link duration prediction is one of the most fundamental problems in vehicular ad hoc networks (VANETs) as it determines the network performance of many vehicular applications. Existing analytical analysis about link duration in both mobile ad hoc network (MANETs) and VANETs is too complicated to be applied in a practical setting. Assuming vehicle's velocity follows the normal distribution, we propose a practical model which considers the distribution of relative velocity, intervehicle distance, and impact of traffic lights to estimate the expected link duration between any pair of connected vehicles. Such model is implemented on each vehicle along with (1) a relative velocity estimation approach and (2) an exponential moving average-(EMA-) based data processing procedure. Furthermore, the proposed model assumes that the events of two consecutive vehicles encountering traffic lights combination are dependent, which make the model more practical. Simulation results show that the link duration model predicts link duration with the average accuracy of 10% and 20% in highway and city scenarios, respectively.
In REF , Wang et al. present the LDP model to estimate the link duration in VANETs, in both urban and highway scenarios.
Practical Link Duration Prediction Model in Vehicular Ad Hoc Networks
International Journal of Distributed Sensor Networks
Computer Science