[1]李世豪,曾锃,缪巍巍,等.基于云边协同的电力物联终端数据轻量化处理方法[J].计算机技术与发展,2024,34(09):23-29.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0182]
　LI Shi-hao,ZENG Zeng,MIAO Wei-wei,et al.Lightweight Processing Method for Power IoT Terminal Data Based on Cloud Edge Collaboration[J].,2024,34(09):23-29.[doi:10.20165/j.cnki.ISSN1673-629X.2024.0182]
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基于云边协同的电力物联终端数据轻量化处理方法()

《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
34
期数:
2024年09期
页码:
23-29
栏目:
大数据与云计算
出版日期:
2024-09-10

文章信息/Info

Title:
Lightweight Processing Method for Power IoT Terminal Data Based on Cloud Edge Collaboration
文章编号:
1673-629X(2024)09-0023-07
作者:
李世豪1; 曾锃1; 缪巍巍1; 夏元轶1; 周忠冉2; 张俊杰2
1. 国网江苏省电力有限公司信息通信分公司,江苏 南京 210024;2. 南瑞集团有限公司,江苏 南京 215200
Author(s):
LI Shi-hao1; ZENG Zeng1; MIAO Wei-wei1; XIA Yuan-yi1; ZHOU Zhong-ran2; ZHANG Jun-jie2
1. Information & Communication Branch,State Grid Jiangsu Electric Power Co. ,Ltd. ,Nanjing 210024,China;2. NARI Group Corporation,Nanjing 215200,China
关键词:
电力物联网; 云边协同; 数据压缩; 边缘计算; 智慧物联; 多元感知
Keywords:
Electric Internet of Things; cloud edge collaboration; data compression; edge computing; smart IoT; multiple perception
分类号:
TP301.5
DOI:
10.20165/j.cnki.ISSN1673-629X.2024.0182
摘要:
电力物联网在大规模化高频数据传输应用中,由于现场存在海量实时数据传输,因而会造成对现场数据无法进行有效压缩,进而导致云边信息传输效率低以及传输流量费用高等问题。 该文提出一种基于云边协同的电力物联数据轻量化处理方法(LPCE)。 该方法基于一种物模型结构,通过提取云边交互数据形成压缩字典,并将压缩字典同步至边缘设备来完成海量数据压缩。 针对传统常见的压缩方法,该文在数据有效率、压缩率、压缩时间以及压缩速度和解压缩速度等方面分别做了对比分析实验。 实验结果表明,在面对高频、实时传输的电力物联网系统中以 JSON(JavaScript Object Notation)格式报文数据为代表的交互数据的压缩,提出的 LPCE 方法具有明显效果和优势。 该方法实现了电力物联网云边数据无损压缩,可减少电力物联网云边之间的冗余数据传输,提升了云边数据传输效率,降低了云边之间数据传输成本。
Abstract:
In the large-scale high-frequency data transmission application of the power Internet of Things (IoT),due to the massive real-time data transmission on site,it will cause the inability to effectively compress on-site data,resulting in low efficiency of cloud edge in-formation transmission and high transmission flow costs. We propose a lightweight processing method for power IoT data based on cloud edge collaboration (LPCE). This method is based on an object model structure,which extracts cloud edge interaction data to form a compression dictionary,and synchronizes the compression dictionary to edge devices to complete massive data compression. We conduct comparative analysis experiments on traditional common compression methods in terms of data efficiency,compression rate,compression time,compression speed, and decompression speed. The experimental results show that the LPCE method proposed has significant effectiveness and advantages in compressing interactive data represented by JSON ( JavaScript Object Notation) format message data in high-frequency and real-time transmission power Internet of Things systems. The proposed method achieves lossless compression of cloud edge data in the power Internet of Things,which can reduce redundant data transmission between cloud edges,improve cloud edge data transmission efficiency,and reduce data transmission costs between cloud edges.

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更新日期/Last Update: 2024-09-10