Device Data Ingestion for Industrial Big Data Platforms with a Case Study

被引：32
|
作者：
Ji, Cun [1 ]
Shao, Qingshi [1 ]
Sun, Jiao [1 ]
Liu, Shijun [1 ,2 ]
Pan, Li [1 ,2 ]
Wu, Lei [1 ,3 ]
Yang, Chenglei [1 ,2 ]
机构：
[1] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China
[2] Shandong Univ, Engn Res Ctr Digital Media Technol, Jinan 250101, Peoples R China
[3] North China Univ Technol, Beijing Key Lab Integrat & Anal Large Scale Strea, Beijing 100144, Peoples R China
来源：
SENSORS | 2016年 / 16卷 / 03期
基金：
国家高技术研究发展计划(863计划); 中国国家自然科学基金;
关键词：
device data ingestion; big data; internet of things; industrial internet of things; INTERNET;
D O I：
10.3390/s16030279
中图分类号：
O65 [分析化学];
学科分类号：
070302 ; 081704 ;
摘要：
Despite having played a significant role in the Industry 4.0 era, the Internet of Things is currently faced with the challenge of how to ingest large-scale heterogeneous and multi-type device data. In response to this problem we present a heterogeneous device data ingestion model for an industrial big data platform. The model includes device templates and four strategies for data synchronization, data slicing, data splitting and data indexing, respectively. We can ingest device data from multiple sources with this heterogeneous device data ingestion model, which has been verified on our industrial big data platform. In addition, we present a case study on device data-based scenario analysis of industrial big data.
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收藏
页数：15
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