Framework Design of an Edge Gateway System Supporting Multi-Protocol Standardized Access Detection

IF 0.7 Q4 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Xiaoyan Zhao, Rui Chen, Jianwei Li, Chunlei Li, Yan Chen, Tian-yao Zhang, Z. Zhang
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引用次数: 0

Abstract

Recently, intelligent city construction has been promoted with the development of the Internet of things (IoT). The edge IoT gateway plays a critical role as the data aggregation core and processing center. Most existing gateways mainly solve heavy data storage and processing loads in cloud computing centers. There is less attention paid to multi-protocol data transmission and fusion. However, multiple products with different protocols in an IoT system require a flexible gateway compatible with multiple protocols. This paper proposes a multi-protocol edge gateway. The frame design was based on the actual demand for edge data acquisition. The gateway hardware platform used an RK3399 chip transplanted from the embedded operating system. It could support simultaneous multi-protocol access to ZigBee, LoRa, Bluetooth, and Wi-Fi. We combined the plug-and-play (PnP) hardware device access detection scheme with the system onboard interface driver to realize dynamic access detection and unified device management. In addition, the gateway also integrated data storage and access functions and partial edge computing functions. Finally, the experiment results verified that the multi-protocol edge gateway could meet the demand for data access and device control.
支持多协议标准化接入检测的边缘网关系统框架设计
近年来,随着物联网(IoT)的发展,智慧城市建设得到了推动。边缘物联网网关作为数据汇聚核心和处理中心,发挥着至关重要的作用。现有的网关主要解决云计算中心的数据存储和处理负荷。对多协议数据传输和融合的研究较少。然而,在物联网系统中,不同协议的多种产品需要灵活兼容多种协议的网关。本文提出了一种多协议边缘网关。框架的设计是基于边缘数据采集的实际需求。网关硬件平台采用嵌入式操作系统移植的RK3399芯片。它可以同时支持对ZigBee、LoRa、蓝牙和Wi-Fi的多协议访问。我们将即插即用(PnP)硬件设备访问检测方案与系统板载接口驱动程序相结合,实现了动态访问检测和统一设备管理。此外,网关还集成了数据存储访问功能和部分边缘计算功能。最后,实验结果验证了多协议边缘网关能够满足数据访问和设备控制的需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
1.50
自引率
14.30%
发文量
89
期刊介绍: JACIII focuses on advanced computational intelligence and intelligent informatics. The topics include, but are not limited to; Fuzzy logic, Fuzzy control, Neural Networks, GA and Evolutionary Computation, Hybrid Systems, Adaptation and Learning Systems, Distributed Intelligent Systems, Network systems, Multi-media, Human interface, Biologically inspired evolutionary systems, Artificial life, Chaos, Complex systems, Fractals, Robotics, Medical applications, Pattern recognition, Virtual reality, Wavelet analysis, Scientific applications, Industrial applications, and Artistic applications.
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