An Efficient Cross-Layer Coding-Assisted Heterogeneous Data Access in Vehicular Networks

Abstract

Recently, much attentions have been paid to network coding-assisted data broadcast in vehicular networks. However, majority of the works consider all the accessed data items are the same size. In this work, we have studied the network coding-assisted heterogeneous on-demand data access in vehicular networks. Firstly, we have investigated the less efficiency of conventional coding assisted approach in accessing heterogeneous data items in real-time vehicular environment. Due to ignoring the impact of heterogeneous data items in decoding, the conventional coding does not achieve expected performance in accessing data items with diverse size. Secondly, based on our observations, we have proposed a new algorithm. The proposed network coding assisted approach exploits the different MCSs (Modulation and coding schemes) of IEEE 802.11p physical layer for leveraging the variable serving rate considering the dynamic positions' of vehicles along with the vehicle mobility. Thirdly, we have built a vehicular simulation environment and evaluated the performance of the proposed approach along with competitive no-coding and coding-assisted approaches under various circumstances. The results show that the proposed approach outperforms the state-of-the-art approaches in terms of improving the on-demand requests serving capability and reducing the data access time.