4.7 Article

Traffic Differentiated Clustering Routing in DSRC and C-V2X Hybrid Vehicular Networks

Journal

IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
Volume 69, Issue 7, Pages 7723-7734

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TVT.2020.2990174

Keywords

Computer architecture; Delays; Quality of service; Routing; Data collection; Optimization; Bandwidth; Dedicated short range communication; cellular-vehicle-to-everything; software defined vehicular networking; clustering; routing optimization

Funding

  1. National Key R&D Program of China [2018YFE0206800]
  2. National Nature Science Foundation of China [61775033, 61771120]
  3. Fundamental Research Funds for the Central Universities [N171602002]

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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.

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