Volume 33, Issue 7 e4499
RESEARCH ARTICLE

Roadside units plane optimization scheme in software-defined vehicular networks

Ming Mao

Corresponding Author

Ming Mao

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

Correspondence

Ming Mao, People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou 450001, China.

Email: [email protected]

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Peng Yi

Peng Yi

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

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Jianhui Zhang

Jianhui Zhang

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

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Liang Wang

Liang Wang

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

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Yuan Gu

Yuan Gu

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

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Guanying Zhang

Guanying Zhang

People's Liberation Army Strategic Support Force Information Engineering University, Zhengzhou, Henan province, China

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First published: 01 April 2022
Citations: 3

Funding information: National Natural Science Foundation of China, 61802429; 61872382; 61521003; National Key R&D Program of China, 2018YFB0804002; 2019YFB1802505; 2019YFB1802501; 2019YFB1802502; 2020YFB1804803

Abstract

As a new research field, software-defined vehicular networks (SDVN) provide a novel idea for the network management of the internet of vehicles. Due to the time-sensitivity of vehicle edge networks, time delay optimization for flow rule management is of great significance to improve system performance. Some existing SDVN architectures select part of the underlying roadside units (RSUs) as underlying controllers to assist the upper control plane. There is no mention of how to optimize the state switching between the RSU controller and the common RSU, which may increase the delay and communication overhead. This paper proposes an RSU plane optimization scheme to reduce the state fluctuation between RSUs with control functions. Firstly, we propose a state fluctuation optimization model of the RSU plane. Secondly, the division method and dynamic adjustment strategy of the RSU plane are designed. Finally, a position prediction method is utilized to realize the pre-installation of flow rules. We use two common methods (greedy and dynamic schemes) to compare with the minimum state fluctuation approach. The simulation analyzes the performance using four parameters. Under the same conditions, the proposed scheme can reduce the flow setup delay and end-to-end delay, while reducing the number of controllers and overhead.

CONFLICT OF INTEREST

The authors declare that they have no conflicts of interest to report regarding the present study.

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available from the corresponding author upon reasonable request.

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