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Improving the Convergence Period of Adaptive Data Rate in a Long Range Wide Area Network for the Internet of Things Devices

Author

Listed:
  • Khola Anwar

    (Department of Physical & Numerical Science, Qurtuba University of Science & Information Technology, Peshawar 25000, Pakistan)

  • Taj Rahman

    (Department of Physical & Numerical Science, Qurtuba University of Science & Information Technology, Peshawar 25000, Pakistan)

  • Asim Zeb

    (Department of Computer Science, Abbottabad University of Science and Technology, Abbottabad 22500, Pakistan)

  • Yousaf Saeed

    (Department of Information Technology, The University of Haripur, Haripur 22620, Pakistan)

  • Muhammad Adnan Khan

    (Pattern Recognition and Machine Learning Lab, Department of Software, Gachon University, Seongnam 13557, Korea
    Faculty of Computing, Lahore Campus, Riphah School of Computing and Innovation, Riphah International University, Lahore 54000, Pakistan)

  • Inayat Khan

    (Department of Computer Science, University of Buner, Buner 19290, Pakistan)

  • Shafiq Ahmad

    (Industrial Engineering Department, College of Engineering, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Abdelaty Edrees Abdelgawad

    (Industrial Engineering Department, King Saud University, P.O. Box 800, Riyadh 11421, Saudi Arabia)

  • Mali Abdollahian

    (School of Science, College of Science, Technology, Engineering, Mathematics, RMIT University, GPO Box 2476, Melbourne, VIC 3001, Australia)

Abstract

A Long-Range Wide Area Network (LoRaWAN) is one of the most efficient technologies and is widely adopted for the Internet of Things (IoT) applications. The IoT consists of massive End Devices (EDs) deployed over large geographical areas, forming a large environment. LoRaWAN uses an Adaptive Data Rate (ADR), targeting static EDs. However, the ADR is affected when the channel conditions between ED and Gateway (GW) are unstable due to shadowing, fading, and mobility. Such a condition causes massive packet loss, which increases the convergence time of the ADR. Therefore, we address the convergence time issue and propose a novel ADR at the network side to lower packet losses. The proposed ADR is evaluated through extensive simulation. The results show an enhanced convergence time compared to the state-of-the-art ADR method by reducing the packet losses and retransmission under dynamic mobile LoRaWAN network.

Suggested Citation

  • Khola Anwar & Taj Rahman & Asim Zeb & Yousaf Saeed & Muhammad Adnan Khan & Inayat Khan & Shafiq Ahmad & Abdelaty Edrees Abdelgawad & Mali Abdollahian, 2021. "Improving the Convergence Period of Adaptive Data Rate in a Long Range Wide Area Network for the Internet of Things Devices," Energies, MDPI, vol. 14(18), pages 1-14, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5614-:d:630744
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    Cited by:

    1. Rachel Kufakunesu & Gerhard P. Hancke & Adnan M. Abu-Mahfouz, 2024. "Collision Avoidance Adaptive Data Rate Algorithm for LoRaWAN," Future Internet, MDPI, vol. 16(10), pages 1-19, October.

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