Vol.35, No.1, 2023, pp.727-737, doi:10.32604/iasc.2023.027563
OPEN ACCESS
ARTICLE
Data Aggregation-based Transmission Method in Ultra-Dense Wireless Networks
  • Dae-Young Kim, Seokhoon Kim*
Department of Computer Software Engineering, Soonchunhyang University, Asan, 31538, Korea
* Corresponding Author: Seokhoon Kim. Email:
Received 20 January 2022; Accepted 13 March 2022; Issue published 06 June 2022
Abstract
As the Internet of Things (IoT) advances, machine-type devices are densely deployed and massive networks such as ultra-dense networks (UDNs) are formed. Various devices attend to the network to transmit data using machine-type communication (MTC), whereby numerous, various are generated. MTC devices generally have resource constraints and use wireless communication. In this kind of network, data aggregation is a key function to provide transmission efficiency. It can reduce the number of transmitted data in the network, and this leads to energy saving and reducing transmission delays. In order to effectively operate data aggregation in UDNs, it is important to select an aggregation point well. The total number of transmitted data may vary, depending on the aggregation point to which the data are delivered. Therefore, in this paper, we propose a novel data aggregation scheme to select the appropriate aggregation point and describe the data transmission method applying the proposed aggregation scheme. In addition, we evaluate the proposed scheme with extensive computer simulations. Better performances in the proposed scheme are achieved compared to the conventional approach.
Keywords
Data aggregation; data transmission; ultra-dense network; machine-type communication; Internet of Things
Cite This Article
D. Kim and S. Kim, "Data aggregation-based transmission method in ultra-dense wireless networks," Intelligent Automation & Soft Computing, vol. 35, no.1, pp. 727–737, 2023.
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.