Provisioned Data Distribution for Intelligent Manufacturing via Fog Computing

被引:5
作者
Sherlekar, Riddhiman [1 ]
Starly, Binil [1 ]
Cohen, Paul H. [1 ]
机构
[1] North Carolina State Univ, Edwards P Fitts Dept Ind & Syst Engn, Raleigh, NC 27695 USA
来源
47TH SME NORTH AMERICAN MANUFACTURING RESEARCH CONFERENCE (NAMRC 47) | 2019年 / 34卷
关键词
Fog Computing; MTConnect Industry 4.0; IIoT; Industrial Cyber-Physical Systems; Big Data; Digital Manufacturing; Data Distribution; ARCHITECTURE; INTERNET; PARADIGM; CLOUD;
D O I
10.1016/j.promfg.2019.06.158
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The number of 'things' ranging from simple devices to complex machines on the factory floor connected at the enterprise level and to the broader internet is growing exponentially. This connection also leads to a tremendous amount of data generated leading to 'Data' now considered one of the core assets in the broader manufacturing industry. However, the availability of this asset is hardly made use of by Small and Medium scale manufacturing enterprises (SME) - the 'Mittelstand' of America. How can certain types of data be shared by SME companies, yet have the ability to retain ownership and control over their own data? How does SME leverage computing on these diverse forms of data for the benefit of its clients and itself? In this paper, we propose a decentralized data distribution architecture to democratize the potential availability of large amounts of data generated by the manufacturing industry using the Fog Computing paradigm. The architecture leverages an Industry scalable middleware extension of Cloud manufacturing that securely filters and transmits data from IoT enabled manufacturing machines on the shop floor to potential users over the cloud. This work also demonstrates a data-centric approach which allows peer-to-peer data sharing laterally within the fog layer to serve cloud users. We demonstrate the feasibility of the Fog middleware infrastructure through case studies that involves various types of manufacturing data. (C) 2019 The Authors. Published by Elsevier B.V.
引用
收藏
页码:893 / 902
页数:10
相关论文
共 44 条
[1]   Fog Computing Architecture, Evaluation, and Future Research Directions [J].
Aazam, Mohammad ;
Zeadally, Sherali ;
Harras, Khaled A. .
IEEE COMMUNICATIONS MAGAZINE, 2018, 56 (05) :46-52
[2]   A Research Perspective on Fog Computing [J].
Bermbach, David ;
Pallas, Frank ;
Garcia Perez, David ;
Plebani, Pierluigi ;
Anderson, Maya ;
Kat, Ronen ;
Tai, Stefan .
SERVICE-ORIENTED COMPUTING - ICSOC 2017 WORKSHOPS, 2018, 10797 :198-210
[3]  
Bonomi F., 2012, Proceedings of the first edition of the MCC workshop on Mobile cloud computing, P13, DOI [DOI 10.1145/2342509.2342513, 10.1145/2342509.2342513]
[4]  
Bonomi F., 2014, Big Data and Internet of Things: A Roadmap for Smart Environments, P169
[5]  
Calo SB, 2017, IEEE INT CONF BIG DA, P3012, DOI 10.1109/BigData.2017.8258272
[6]  
Cao Y, 2015, PROCEEDINGS OF THE 2015 IEEE INTERNATIONAL CONFERENCE ON NETWORKING, ARCHITECTURE AND STORAGE (NAS), P2, DOI 10.1109/NAS.2015.7255196
[7]   Utility-Driven Data Management for Data-Intensive Applications in Fog Environments [J].
Cappiello, Cinzia ;
Pernici, Barbara ;
Plebani, Pierluigi ;
Vitali, Monica .
ADVANCES IN CONCEPTUAL MODELING, ER 2017, 2017, 10651 :216-226
[8]   Computer-Integrated Manufacturing, Cyber-Physical Systems and Cloud Manufacturing - Concepts and relationships [J].
Yu, Chunyang ;
Xu, Xun ;
Lu, Yuqian .
Manufacturing Letters, 2015, 6 :5-9
[9]  
Clemente J, 2017, 2017 IEEE FOG WORLD CONGRESS (FWC), P116
[10]  
Data B., 2014, PRINCIPLES BEST PRAC