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An Environmentally Sustainable Software-Defined Networking Data Dissemination Method for Mixed Traffic Flows in RSU Clouds with Energy Restriction

Author

Listed:
  • Hongming Li

    (Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Dongxiu Ou

    (Key Laboratory of Railway Industry of Proactive Safety and Risk Control, School of Transportation Engineering, Tongji University, Shanghai 201804, China)

  • Yuqing Ji

    (Key Laboratory of Road and Traffic Engineering, Ministry of Education, School of Transportation Engineering, Tongji University, Shanghai 201804, China)

Abstract

The connected multi road side unit (RSU) environment can be envisioned as the RSU cloud. In this paper, the Software-Defined Networking (SDN) framework is utilized to dynamically reconfigure the RSU clouds for the mixed traffic flows with energy restrictions, which are composed of five categories of vehicles with distinctive communication demands. An environmentally sustainable SDN data dissemination method for safer and greener transportation solutions is thus proposed, aiming to achieve the lowest overall SDN cloud delay with the least working hosts and minimum energy consumption, which is a mixed integer linear programming problem (MILP). To solve the problem, Joint optimization algorithms with Finite resources (JF) in three hyperparameters versions, JF (DW = 0.3, HW = 0.7), JF (DW = 0.5, HW = 0.5) and JF (DW = 0.7, HW = 0.3), were proposed, which are in contrast with single-objective optimization algorithms, the Host Optimization (H) algorithm, and the Delay optimization (D) algorithm. Results show that JF (DW = 0.3, HW = 0.7) and JF (DW = 0.5, HW = 0.5), when compared with the D algorithm, usually had slightly larger cloud delays, but fewer working hosts and energy consumptions, which has vital significance for enhancing energy efficiency and environmental protection, and shows the superiority of JFs over the D algorithm. Meanwhile, the H algorithm had the least working hosts and fewest energy consumptions under the same conditions, but completely ignored the explosive surge of delay, which is not desirable for most cases of the SDN RSU cloud. Further analysis showed that the larger the network topology of the SDN cloud, the harder it was to find a feasible network configuration. Therefore, when designing an environmentally sustainable SDN RSU cloud for the greener future mobility of intelligent transportation systems, its size should be limited or partitioned into a relatively small topology.

Suggested Citation

  • Hongming Li & Dongxiu Ou & Yuqing Ji, 2022. "An Environmentally Sustainable Software-Defined Networking Data Dissemination Method for Mixed Traffic Flows in RSU Clouds with Energy Restriction," IJERPH, MDPI, vol. 19(22), pages 1-21, November.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:22:p:15112-:d:974612
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    References listed on IDEAS

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    1. Weiwu Wang & Huan Chen & Lizhong Wang & Xinyu Li & Danyi Mao & Shan Wang, 2022. "Exploration of Spatio-Temporal Characteristics of Carbon Emissions from Energy Consumption and Their Driving Factors: A Case Analysis of the Yangtze River Delta, China," IJERPH, MDPI, vol. 19(15), pages 1-25, August.
    2. Li Yang & Sumaiya Bashiru Danwana & Fadilul-lah Yassaanah Issahaku, 2022. "Achieving Environmental Sustainability in Africa: The Role of Renewable Energy Consumption, Natural Resources, and Government Effectiveness—Evidence from Symmetric and Asymmetric ARDL Models," IJERPH, MDPI, vol. 19(13), pages 1-26, June.
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