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The reliable routing for software-defined vehicular networks towards beyond 5G

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Abstract

An extension of Software-Defined Networking (SDN) to the vehicular networks can improve the network performance effectively. However, with the explosive growth of vehicles, the architecture of Software-Defined Vehicular Networks (SDVNs) cannot well satisfy the stringent end-to-end latency requirement of vehicles. To cope with the problem, The 5G has been regarded as a promising technology to be integrated into SDVNs. However, there are still some technical challenges in 5G, such as coverage issues, which limit the development of vehicular networks. Beyond 5G (B5G) technology is envisioned as a promising solution to expand the capabilities of vehicular networks in terms of safety, reliability, etc. In this paper, we introduce B5G technology to improve the SDVNs to implement reliable routing. Firstly, we propose a new architecture of SDVNs based on B5G technology, and creat a protocol stack which integrates the 5G protocol into the WAVE protocol. In addition, we design the adaptive link performance monitoring mechanism which balances the control overhead and the accuracy. Finally, we improve the Genetic Algorithm (GA) through cross-generation selection and small-environment strategy and design an reliable QoS routing algorithm. The simulation results demonstrate that the monitoring mechanism can measure the performance of the link more accurately, and the improved GA is superior to standard GA and Dijkstra. In particular, compared with the standard GA, the improved GA can improve bandwidth utilization, delay, and packet loss rate by 34.3%, 30.6%, and 20.9%, respectively.

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Acknowledgements

This work is supported by the National Key R&D Program of China under Grant No. 2019YFB1802800, the Major International(Regional) Joint Research Project of NSFC under Grant No. 71620107003, the National Natural Science Foundation of China under Grant No. 62032013 and No. 61872073, the LiaoNing Revitalization Talents Program under Grant No. XLYC1902010.

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Authors and Affiliations

  1. College of Computer Science and Engineering, Northeastern University, Shenyang, 110169, China

    Yaoguang Lu, Xingwei Wang & Bo Yi

  2. College of Information Science and Engineering, State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang, 110819, China

    Min Huang

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  1. Yaoguang Lu
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Correspondence to Yaoguang Lu.

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Lu, Y., Wang, X., Yi, B. et al. The reliable routing for software-defined vehicular networks towards beyond 5G. Peer-to-Peer Netw. Appl. 15, 134–148 (2022). https://doi.org/10.1007/s12083-021-01231-1

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