Table of Content

Open Access iconOpen Access

ARTICLE

crossmark

Adaptive Data Transmission Method According to Wireless State in Long Range Wide Area Networks

Seokhoon Kim1, Dae-Young Kim2, *

1 Department of Computer Software Engineering, Soonchunhyang University, Asan-si, 31538, Korea.
2 School of Computer Software, Daegu Catholic University, Gyeongsan-si, 38430, Korea.

* Corresponding Author: Dae-Young Kim. Email: email.

Computers, Materials & Continua 2020, 64(1), 1-15. https://doi.org/10.32604/cmc.2020.09545

Abstract

The Internet of Things (IoT) has enabled various intelligent services, and IoT service range has been steadily extended through long range wide area communication technologies, which enable very long distance wireless data transmission. End-nodes are connected to a gateway with a single hop. They consume very low-power, using very low data rate to deliver data. Since long transmission time is consequently needed for each data packet transmission in long range wide area networks, data transmission should be efficiently performed. Therefore, this paper proposes a multicast uplink data transmission mechanism particularly for bad network conditions. Transmission delay will be increased if only retransmissions are used under bad network conditions. However, employing multicast techniques in bad network conditions can significantly increase packet delivery rate. Thus, retransmission can be reduced and hence transmission efficiency increased. Therefore, the proposed method adopts multicast uplink after network condition prediction. To predict network conditions, the proposed method uses a deep neural network algorithm. The proposed method performance was verified by comparison with uplink unicast transmission only, confirming significantly improved performance.

Keywords


Cite This Article

S. Kim and D. Kim, "Adaptive data transmission method according to wireless state in long range wide area networks," Computers, Materials & Continua, vol. 64, no.1, pp. 1–15, 2020. https://doi.org/10.32604/cmc.2020.09545

Citations




cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 2481

    View

  • 1449

    Download

  • 0

    Like

Share Link