A Mobility-Predict-based Forwarding Strategy in Vehicular Named Data Networks

Abstract

Named data networking (NDN) is promising for Vehicular Ad hoc Networks (VANETs) owing to its data-centric communication paradigm. However, the existing forwarding strategies for vehicular named data networks (VNDN) cannot handle well the issues of high mobility and broadcast storm. In this paper, we propose a Mobility-Predict-based Forwarding Strategy (MPFS) to tackle these issues in VNDN. First, in order to solve the problem of outdated mobility information in the neighbor table, a lightweight but highly effective approach is proposed to predict the current position in MPFS. Then, the predicted mobility information of the vehicles in the neighbor table is applied to select the next-hop forwarder(s) in both directions (road direction and reverse road direction) of the consumer. Furthermore, the vehicle that is farthest from the current forwarder with a stable link is considered as the next-hop forwarder. Finally, extensive simulations are carried out to demonstrate that MPFS has a less number of Interest packets forwarded, while maintaining a higher ratio of satisfied Interest packets compared with the baseline forwarding strategies.