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计算机系统应用英文版:2022,31(5):85-93
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面向IoT的边缘节点平台架构
(1.贵州大学 计算机科学与技术学院, 贵阳 550025;2.贵州大学 省部共建公共大数据国家重点实验室(筹), 贵阳 550025;3.贵州财经大学 信息学院, 贵阳 550025;4.国家电网浙江省电力有限公司, 杭州 310007)
IoT-oriented Edge Node Platform Architecture
(1.School of Computer Science and Technology, Guizhou University, Guiyang 550025, China;2.State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China;3.School of Information, Guizhou University of Finance and Economics, Guiyang 550025, China;4.State Grid Zhejiang Electric Power Co. Ltd., Hangzhou 310007, China)
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Received:August 09, 2021    Revised:September 13, 2021
中文摘要: 针对边缘节点体系结构支持功能单一、模块划分混乱、向云端传输数据中的带宽开销大以及数据传输安全问题, 设计开发了一套面向IoT的边缘节点平台架构. 该平台架构包括设备管理、数据管理、资源管理、应用管理以及导出服务管理5个模块, 使用最小二乘法等算法在边缘侧实现数据采集、数据过滤、数据加密、指标分析等功能. 测试结果表明, 该平台能够无间断收集周围环境信息, 分析环境数据, 能够降低边缘侧向云端传输数据的成本, 同时保证数据安全可靠传输.
Abstract:The structure of the edge node system is exposed to problems of the single function, the confusing module division, and the high bandwidth overhead, and security risks in edge-to-cloud data transmission. To solve these problems, this study designs and develops an IoT-oriented edge node platform architecture. The platform architecture consists of five modules, i.e., device management, data management, resource management, application management, and exporting service management. The designed platform architecture applies algorithms such as the least square method to achieve functions including data collection, data filtering, data encryption, and indicator analysis on the edge side. The experimental results indicate that the platform can continuously collect surroundings information, filter and analyze data, and ensure the safe and reliable transmission of data while reducing the cost of edge-to-cloud data transmission.
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基金项目:国家自然科学基金(61902085); 贵州省科技计划(黔科合基础[2020]1Y267); 贵州大学引进人才科研项目(贵大人基合字(2019)52号)
引用文本:
邢照庆,崔允贺,吕晓丹,钱清,申国伟,赵建朋.面向IoT的边缘节点平台架构.计算机系统应用,2022,31(5):85-93
XING Zhao-Qing,CUI Yun-He,LYU Xiao-Dan,QIAN Qing,SHEN Guo-Wei,ZHAO Jian-Peng.IoT-oriented Edge Node Platform Architecture.COMPUTER SYSTEMS APPLICATIONS,2022,31(5):85-93