Internet of Things (IoT) devices and technologies utilizing it are becoming popular all over the world. In addition, IoT devices are installed in various fields, and thus they are used in a wide area. Therefore, we need a network capable of supporting wide area and transmitting / receiving small IoT...
Internet of Things (IoT) devices and technologies utilizing it are becoming popular all over the world. In addition, IoT devices are installed in various fields, and thus they are used in a wide area. Therefore, we need a network capable of supporting wide area and transmitting / receiving small IoT data. To support this, LPWAN (Low Power Wide Area Network), which is a network used in IoT supporting a wide area of low power, has appeared. LoRaWAN is a practical implementation of LPWAN and is used in many European countries. It can support a range of hundreds of square kilometers with a single gateway. However, due to the limitation of the LoRaWAN MAC protocol, it is difficult to apply it to the real-time monitoring required in some IoT fields. In this paper, we propose two methods to solve this problem and explain the methods through the experimental results.
Before explaining the proposed method, we first provide an overview of LoRa and LoRaWAN, and explain the limitations that LoRaWAN does not apply to real-time monitoring. In this paper, we propose two methods to change the data rate periodically according to the Adaptive Data Rate algorithm of LoRaWAN and to check the collision rate of traffic and to use redundant channels by IoT nodes. In this paper, we describe two methods in more detail and describe scenarios in which real-time monitoring is applied. After that, we introduce the LoRa and LoRaWAN testbed constructed using actual Open Hardware such as Arduino and Raspberry Pi before proceeding with the experiment applying the proposed method. Then, the proposed method is applied to the actual LoRaWAN MAC Protocol, and the performance is evaluated and compared with the existing environment. Finally, the results obtained through the proposed method will be discussed and the necessary research will be described in the future.
Internet of Things (IoT) devices and technologies utilizing it are becoming popular all over the world. In addition, IoT devices are installed in various fields, and thus they are used in a wide area. Therefore, we need a network capable of supporting wide area and transmitting / receiving small IoT data. To support this, LPWAN (Low Power Wide Area Network), which is a network used in IoT supporting a wide area of low power, has appeared. LoRaWAN is a practical implementation of LPWAN and is used in many European countries. It can support a range of hundreds of square kilometers with a single gateway. However, due to the limitation of the LoRaWAN MAC protocol, it is difficult to apply it to the real-time monitoring required in some IoT fields. In this paper, we propose two methods to solve this problem and explain the methods through the experimental results.
Before explaining the proposed method, we first provide an overview of LoRa and LoRaWAN, and explain the limitations that LoRaWAN does not apply to real-time monitoring. In this paper, we propose two methods to change the data rate periodically according to the Adaptive Data Rate algorithm of LoRaWAN and to check the collision rate of traffic and to use redundant channels by IoT nodes. In this paper, we describe two methods in more detail and describe scenarios in which real-time monitoring is applied. After that, we introduce the LoRa and LoRaWAN testbed constructed using actual Open Hardware such as Arduino and Raspberry Pi before proceeding with the experiment applying the proposed method. Then, the proposed method is applied to the actual LoRaWAN MAC Protocol, and the performance is evaluated and compared with the existing environment. Finally, the results obtained through the proposed method will be discussed and the necessary research will be described in the future.
Keyword
#LPWAN(Low Power Wide Area Network), LoRaWAN, LoRa, IoT, Real-Time Monitoring, Open Hardware, Arduino, Raspberry Pi, Open Source
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