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Remote Monitoring Systems of Unsafe Software Execution using QR Code-based Power Consumption Profile for IoT Edge Devices

机译:使用基于QR码的功耗配置文件的远程监控系统的无安全软件执行用于IOT边缘设备

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If an error occurs in a system where several edges are gathered and operated together, the error may be transferred to other edges or the entire system may be down. Therefore, it is important to judge and control the errors of each edge in such a system, which puts a load on the embedded system of small edges. However, it is not easy to judge an error in an embedded system with limitations of performance. In such a system, we try to determine the state of the edge device using power consumption data and determine the error based on it. In this paper, we show that the server can determine errors using the power consumption data, and the data consumption allows the server to read data values through data communication using QR codes. In this architecture, the edge device only transmits power consumption data to reduce the load on the embedded system, and the gateway and server collect the data using QR codes communication. At the same time, the server interprets the received data to determine errors using various algorithms and controls the edge device. In this process, it is important to synchronize the edge device with the gateway and the server. Since the proposed structure uses a separate power meter and communication device, it solves the problem of not sending an appropriate message to the server when a communication error occurs at the previous edge. Also, the proposed model solves the overload problem that occurs when networks are used in various IoT devices using QR code that imaged data and light communication using a camera. After data is extracted and sorted from the QR code obtained by recognizing the camera of the intermediate server, the main server performs error determination through data analysis. The proposed architecture was implemented using ‘chip-whisperer’ to measure edges and data, as well as ‘raspberry pi’ to implement the server. As a result, the proposed architecture server showed successful data transmission and error determination, and it also showed very little additional load at the edge.
机译:如果在一个系统中收集和操作的系统中发生错误,则误差可以被传送到其他边缘,或者整个系统可能会关闭。因此,重要的是在这种系统中判断和控制每个边缘的误差,这对小边缘的嵌入式系统进行了负载。但是,在具有性能局限性的嵌入式系统中判断错误并不容易。在这样的系统中,我们尝试使用功耗数据确定边缘设备的状态,并根据其确定错误。在本文中,我们表明服务器可以使用功耗数据确定错误,并且数据消耗允许服务器通过使用QR码通过数据通信读取数据值。在该架构中,边缘设备仅传输功耗数据以减少嵌入式系统上的负载,并且网关和服务器使用QR码通信收集数据。同时,服务器将接收的数据解释以确定使用各种算法的错误并控制边缘设备。在此过程中,重要的是将边缘设备与网关和服务器同步。由于所提出的结构使用单独的功率计和通信设备,因此当在前一个边缘发生通信错误时,它解决了未向服务器发送适当的消息的问题。此外,所提出的模型解决了在使用QR码中使用的数据和使用相机的光通信的QR码在各种IOT设备中使用的网络时发生的过载问题。在通过识别中间服务器的相机通过识别中间服务器获得的QR码中提取和排序数据之后,主服务器通过数据分析执行错误确定。所提出的架构是使用“芯片 - 低声”来测量边缘和数据的,以及“Raspberry PI”实现服务器。因此,所提出的架构服务器显示了成功的数据传输和错误确定,并且它也显示了边缘处的额外额外的负载。

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