Vehicular Named Data Networking Framework

Abstract

Named Data Networking (NDN) might potentially help improve data acquisition efficiency in vehicular environments, so it is introduced into vehicular networks, namely vehicular NDN (VNDN). In the existing VNDN solutions, a large number of vehicles with high mobility are involved in forwarding messages, so it is hard to achieve request aggregation that is the main advantage of NDN and can help reduce the data acquisition delay. Moreover, the solutions employ flooding to achieve data retrieval without consumer mobility support, which increases the data acquisition cost and reduces the data acquisition success rate. In this paper, we propose a novel VNDN framework and aim to reduce the data acquisition delay and cost and improve the data acquisition success rate. In this framework, the cluster-chain vehicular backbone is constructed to enhance the stability of the backbone topology. Based on cluster chains, consumers can employ request aggregation and unicast to acquire data from the nearest provider. Moreover, consumer mobility is supported to guarantee successful retrieval of data in spite of high mobility of vehicles. This framework is quantitatively evaluated. According to the experimental results, compared with the VNDN approaches, our framework reduces the data acquisition cost and delay by nearly 54.6% and 12.3%, respectively, and improves the data retrieval success rate by nearly 7.9%.