Industrial Edge Computing Enabling Embedded Intelligence

被引:72
|
作者
Dai, Wenbin [1 ,2 ]
Nishi, Hiroaki [3 ,4 ,5 ,6 ]
Vyatkin, Valeriy [7 ,8 ]
Huang, Victor [9 ,10 ]
Shi, Yang [11 ]
Guan, Xinping [12 ,13 ,14 ,15 ]
机构
[1] Shanghai Jiao Tong Univ, Shanghai, Peoples R China
[2] Shanghai Automat Assoc, Shanghai, Peoples R China
[3] Keio Univ, Tokyo, Japan
[4] Smart Community Implementat Comm Musashikosugi, Kawasaki, Kanagawa, Japan
[5] Smart Community Implementat Comm Musashikosugi, Nasushiobara City, Japan
[6] Smart Community Implementat Comm Urawamisono, Saitama, Japan
[7] Lulea Univ Technol, Dept Dependable Computat, Lulea, Sweden
[8] Aalto Univ, Informat Technol Automat, Espoo, Finland
[9] Inst Microelect, Singapores Highly Successful High Technol Ind, Singapore, Singapore
[10] AT&T Bell Labs, Murray Hill, NJ USA
[11] Huawei Technol Co Ltd, Chengdu, Peoples R China
[12] Shanghai Jiao Tong Univ, Shanghai, Peoples R China
[13] Shanghai Jiao Tong Univ, Sch Elect Informat & Elect Engn, Shanghai, Peoples R China
[14] Minist Educ China, Key Lab Syst Control & Informat Proc, Beijing, Peoples R China
[15] Natl Nat Sci Fdn China, Prestigious Innovat Res Team, Beijing, Peoples R China
基金
中国国家自然科学基金; 日本学术振兴会;
关键词
MANAGEMENT;
D O I
10.1109/MIE.2019.2943283
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The term industrial edge computing is used to describe a distributed platform that integrates communication, computation, and storage resources for performing real-time applications that can be directly accessed from the cloud. A step toward the industrial Internet revolution, industrial edge computing is designed to facilitate agile connectivity, real-time control, and data optimization, while enabling intelligent applications, ensuring tight security, and protecting privacy. Industrial edge computing makes use of what is known as edge computing nodes (ECNs), which bridge the gap between the physical world and the digital world by acting as smart gateways for assets, services, and systems. The IEEE P2805 Standards are being developed for defining protocols for self-management, data acquisition, and machine learning through cloud-edge collaboration on ECNs. © 2007-2011 IEEE.
引用
收藏
页码:48 / 56
页数:9
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