Research Area:  Vehicular Ad Hoc Networks
With recent advances in wireless communications, much attentions have been paid to data services in vehicular ad hoc networks (VANETs). Network coding has been considered as a promising approach to improving the bandwidth efficiency in the field of wireless communications. However, due to the heterogeneities of vehicular networks, such as diverse size of data items and different data transmission rates, current data scheduling methods cannot achieve expected performance in heterogenous VANETs. In this paper, we propose a novel system architecture integrated with software defined network (SDN) and fog computing as well as a dedicated algorithm for cooperative data services to enhance performance in heterogeneous VANETs. In particular, first, we present a novel service architecture in heterogeneous VANETs, which integrates both software defined network and fog computing. Then, we formulate a problem called Fog-Assisted Heterogeneous Data Services (FAHDS), which aims to minimize the service delay. In addition, we prove that FAHDS is NP-hard by constructing a polynomial-time reduction from the minimum clique cover (MCC) problem. Further, we propose a greedy algorithm implemented at the SDN controller, which makes coding decisions for cloud nodes and notifies the cooperative operations among fog nodes and vehicles. Finally, a comprehensive simulation is carried out for performance evaluation. The simulation results demonstrate the effectiveness of the proposed architecture and algorithm.
Author(s) Name:  Ke Xiao, Kai Liu, Xincao Xu, Yi Zhou & Liang Feng
Journal name:  Journal of Ambient Intelligence and Humanized Computing
Publisher name:  SPRINGER
Volume Information:  volume 12, pages 261–273 (2021)
Paper Link:   https://link.springer.com/article/10.1007/s12652-019-01507-8