@Article{cmc.2020.09545,
AUTHOR = {Seokhoon Kim, Dae-Young Kim},
TITLE = {Adaptive Data Transmission Method According to Wireless State in Long Range Wide Area Networks},
JOURNAL = {Computers, Materials \& Continua},
VOLUME = {64},
YEAR = {2020},
NUMBER = {1},
PAGES = {1--15},
URL = {http://www.techscience.com/cmc/v64n1/39128},
ISSN = {1546-2226},
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.},
DOI = {10.32604/cmc.2020.09545}
}