Infrastructure-Assisted Markov Prediction Routing Protocol for Urban Scenarios

Abstract

It has been recognized the benefits that utilizing fixed Road Side Units (RSUs) as routing complements to Vehicular Ad-hoc Network (VANET) can improve reliable end to end multi-hop communications. This paper presents Infrastructure-assisted Markov Prediction Routing Protocol (IAMPR) for urban VANET scenarios. IAMPR formulates corresponding routing algorithms for vehicles and RSUs in order to exploit the available heterogeneous network efficiently. Store-and-forward buffering, Markov chains predictor and duplicate transmission techniques are also adopted in the protocol aiming at local minimum problem cause by greedy forwarding strategy. To better evaluate the performance of IAMPR, we complete simulation in NS-3 simulator under a real world topology urban scenario. Simulation results show that our proposed protocol outperforms Greedy V2I2V and GPSR in terms of packet delivery ratio and end to end delay under varying vehicles densities and speeds.