Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks
Lei Guo, Björn Landfeldt, Qingyang Song, Lei Guo, Abbas Jamalipour
Abstract
Vehicles equipped with sensors can participate in mobile crowdsourcing applications. Vehicular Ad Hoc Networks (VANETs) based on Dedicated Short Range Communication (DSRC) are used to carry sensing data. However, multi-hop transmissions for gathering data to Road Side Units (RSUs) in VANETs suffer from low data rate and long end-to-end delay, which can hardly meet the QoS requirements of delay-sensitive services. This triggers the consideration of constituting a DSRC and Cellular-Vehicle-to-Everything (C-V2X) hybrid vehicular network. Nevertheless, using cellular links to carry traffic can cause high cellular bandwidth costs. In this paper, we propose a Traffic Differentiated Clustering Routing (TDCR) mechanism in a Software Defined Network (SDN)-enabled hybrid vehicular network. The proposed mechanism includes a centralized one-hop clustering approach and a data delivery optimization method. Particularly, the optimization is to make a tradeoff between cellular bandwidth cost and end-to-end delay, for Cluster Heads (CHs) delivering their aggregated data either by multi-hop Vehicle-to-Vehicle (V2V) transmissions or by cellular networks. Since the problem is proven to be NP-hard, a two-stage heuristic algorithm is designed. We carry out simulations to evaluate the performance of our data collection scheme and the results show that it performs better than traditional mechanisms.