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Multilevel Service-Provisioning-Based Autonomous Vehicle Applications

Author

Listed:
  • Mashael Khayyat

    (Department of Information Systems and Technology, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia)

  • Abdullah Alshahrani

    (Department of Computer Science and Artificial Intelligence, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia)

  • Soltan Alharbi

    (Department of Computer and Network Engineering, College of Computer Science and Engineering, University of Jeddah, Jeddah 23218, Saudi Arabia)

  • Ibrahim Elgendy

    (School of Computer Science and Technology, Harbin Institute of Technology, No.11 Siling Street, Nangang District, Harbin 150001, China
    Department of Computer Science, Faculty of Computers and Information, Menoufia University, Gamal Abd El-Nasir, Qism Shebeen El-Kom, Shibin el Kom, Menofia Governorate 32511, Egypt)

  • Alexander Paramonov

    (Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint Petersburg State University of Telecommunications, Prospekt Bol’shevikov, 193232 St. Petersburg, Russia)

  • Andrey Koucheryavy

    (Department of Communication Networks and Data Transmission, The Bonch-Bruevich Saint Petersburg State University of Telecommunications, Prospekt Bol’shevikov, 193232 St. Petersburg, Russia)

Abstract

With the recent advances and development of autonomous control systems of cars, the design and development of reliable infrastructure and communication networks become a necessity. The recent release of the fifth-generation cellular system (5G) promises to provide a step towards reliability or a panacea. However, designing autonomous vehicle networks has more requirements due to the high mobility and traffic density of such networks and the latency and reliability requirements of applications run over such networks. To this end, we proposed a multilevel cloud system for autonomous vehicles which was built over the Tactile Internet. In addition, base stations at the edge of the radio-access network (RAN) with different technologies of antennas are used in our system. Finally, simulation results show that the proposed system with multilevel clouding can significantly reduce the round-trip latency and the network congestion. In addition, our system can be adapted in the mobility scenario.

Suggested Citation

  • Mashael Khayyat & Abdullah Alshahrani & Soltan Alharbi & Ibrahim Elgendy & Alexander Paramonov & Andrey Koucheryavy, 2020. "Multilevel Service-Provisioning-Based Autonomous Vehicle Applications," Sustainability, MDPI, vol. 12(6), pages 1-16, March.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:6:p:2497-:d:335728
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    References listed on IDEAS

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    1. Lvhua Wang & Yongxue Liu & Liang Mao & Chao Sun, 2018. "Potential Impacts of China 2030 High-Speed Rail Network on Ground Transportation Accessibility," Sustainability, MDPI, vol. 10(4), pages 1-16, April.
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    3. Heejung Yu & Howon Lee & Hongbeom Jeon, 2017. "What is 5G? Emerging 5G Mobile Services and Network Requirements," Sustainability, MDPI, vol. 9(10), pages 1-22, October.
    4. Peng Jing & Gang Xu & Yuexia Chen & Yuji Shi & Fengping Zhan, 2020. "The Determinants behind the Acceptance of Autonomous Vehicles: A Systematic Review," Sustainability, MDPI, vol. 12(5), pages 1-26, February.
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    Cited by:

    1. Volkov Artem & Kovalenko Vadim & Ibrahim A. Elgendy & Ammar Muthanna & Andrey Koucheryavy, 2021. "DD-FoG: Intelligent Distributed Dynamic FoG Computing Framework," Future Internet, MDPI, vol. 14(1), pages 1-19, December.
    2. Ahmed Al-Ansi & Abdullah M. Al-Ansi & Ammar Muthanna & Ibrahim A. Elgendy & Andrey Koucheryavy, 2021. "Survey on Intelligence Edge Computing in 6G: Characteristics, Challenges, Potential Use Cases, and Market Drivers," Future Internet, MDPI, vol. 13(5), pages 1-23, April.

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