Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things

In order to solve the problem that the existing LoRaWAN adaptive data rate control algorithm leads to low data transmission efficiency in the case of network congestion, a method combining a fuzzy logistic regression classifier and an improved adaptive data rate controller adjusting the avoidance ti...

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Main Author: Zhijie Zhang
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:Journal of Control Science and Engineering
Online Access:http://dx.doi.org/10.1155/2022/4415500
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author Zhijie Zhang
author_facet Zhijie Zhang
author_sort Zhijie Zhang
collection DOAJ
description In order to solve the problem that the existing LoRaWAN adaptive data rate control algorithm leads to low data transmission efficiency in the case of network congestion, a method combining a fuzzy logistic regression classifier and an improved adaptive data rate controller adjusting the avoidance time was proposed. The classifier could obtain the predicted congestion state by logistic regression learning. The data rate controller determined the data rate adjustment scheme according to the predicted congestion state. The experimental results showed that when the network congestion occurred in about 12s, the number of packet loss by the LoRaWAN default method was higher than that by the method in the research. The value of ADR_ MSG_CNT of the 15 source nodes in the method was 30 within 0–10 s, while the RCV_ACK_CNT of some nodes was 0. It proved that the method was more efficient than the original LoRaWAN adaptive data rate control algorithm.
format Article
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institution OA Journals
issn 1687-5257
language English
publishDate 2022-01-01
publisher Wiley
record_format Article
series Journal of Control Science and Engineering
spelling doaj-art-511d723e1a10452d89f76afa608464772025-08-20T02:05:17ZengWileyJournal of Control Science and Engineering1687-52572022-01-01202210.1155/2022/4415500Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of ThingsZhijie Zhang0Beihai Vocational CollegeIn order to solve the problem that the existing LoRaWAN adaptive data rate control algorithm leads to low data transmission efficiency in the case of network congestion, a method combining a fuzzy logistic regression classifier and an improved adaptive data rate controller adjusting the avoidance time was proposed. The classifier could obtain the predicted congestion state by logistic regression learning. The data rate controller determined the data rate adjustment scheme according to the predicted congestion state. The experimental results showed that when the network congestion occurred in about 12s, the number of packet loss by the LoRaWAN default method was higher than that by the method in the research. The value of ADR_ MSG_CNT of the 15 source nodes in the method was 30 within 0–10 s, while the RCV_ACK_CNT of some nodes was 0. It proved that the method was more efficient than the original LoRaWAN adaptive data rate control algorithm.http://dx.doi.org/10.1155/2022/4415500
spellingShingle Zhijie Zhang
Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
Journal of Control Science and Engineering
title Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
title_full Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
title_fullStr Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
title_full_unstemmed Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
title_short Based on Fuzzy Measure Algorithm Message Adaptive Rate Algorithm of Internet of Things
title_sort based on fuzzy measure algorithm message adaptive rate algorithm of internet of things
url http://dx.doi.org/10.1155/2022/4415500
work_keys_str_mv AT zhijiezhang basedonfuzzymeasurealgorithmmessageadaptiveratealgorithmofinternetofthings