Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory

Yohan Han; Byungjun Park; Jongpil Jeong

doi:10.1007/978-3-030-24296-1_5

Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory

Yohan Han
, Byungjun Park
, Jongpil Jeong

Research & Business Foundation

Sungkyunkwan University

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

9 Scopus citations

Abstract

Industrial IoT data analysis is an essential means of obtaining important information in efficient smart factory operation. IoT devices connected to Smart Factory produce large amount of data from variety of mechanical facilities that actually operate. Because the collected data can be analyzed in real time, optimizing plant operations can be optimized, predicting maintenance schedules for mechanical facilities or quickly replacing equipment with faulty ones. In addition, various information needed for efficient operation can be obtained, such as improving the quality of the products produced. Using 5G wireless network and fog node and cloud computing, this paper introduces a new platform that supports efficient analysis of big data collected in smart factories. Leveraging various resources of 5G wireless network, it provides an optimized environment for collecting IoT data such as size, speed, delay and variety. It also provides big data analytic services through fog nodes and cloud computing and addresses various requirements for data collection, processing, analysis and management. This paper describes the requirements and design components of the proposed platform. Introduce case studies using data sets obtained from smart factories to validate the platform and provide meaningful results. The experimental results clearly show the benefits and practicalities of the platform.

Original language	English
Title of host publication	Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings
Editors	Sanjay Misra, Osvaldo Gervasi, Beniamino Murgante, Elena Stankova, Vladimir Korkhov, Carmelo Torre, Eufemia Tarantino, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan
Publisher	Springer Verlag
Pages	44-52
Number of pages	9
ISBN (Print)	9783030242954
DOIs	https://doi.org/10.1007/978-3-030-24296-1_5
State	Published - 2019
Event	19th International Conference on Computational Science and Its Applications, ICCSA 2019 - Saint Petersburg, Russian Federation Duration: 1 Jul 2019 → 4 Jul 2019

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	11620 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	19th International Conference on Computational Science and Its Applications, ICCSA 2019
Country/Territory	Russian Federation
City	Saint Petersburg
Period	1/07/19 → 4/07/19

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 9 Industry, Innovation, and Infrastructure

Keywords

5G-networked Smart Factory
Big data
Cloud computing
Fog computing
Industrial IoT

Access to Document

10.1007/978-3-030-24296-1_5

Cite this

Han, Y., Park, B., & Jeong, J. (2019). Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory. In S. Misra, O. Gervasi, B. Murgante, E. Stankova, V. Korkhov, C. Torre, E. Tarantino, A. M. A. C. Rocha, D. Taniar, & B. O. Apduhan (Eds.), Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings (pp. 44-52). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11620 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-030-24296-1_5

Han, Yohan ; Park, Byungjun ; Jeong, Jongpil. / Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory. Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. editor / Sanjay Misra ; Osvaldo Gervasi ; Beniamino Murgante ; Elena Stankova ; Vladimir Korkhov ; Carmelo Torre ; Eufemia Tarantino ; Ana Maria A.C. Rocha ; David Taniar ; Bernady O. Apduhan. Springer Verlag, 2019. pp. 44-52 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

@inproceedings{21bac7389a86433e8ee21c620efa59a1,

title = "Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory",

abstract = "Industrial IoT data analysis is an essential means of obtaining important information in efficient smart factory operation. IoT devices connected to Smart Factory produce large amount of data from variety of mechanical facilities that actually operate. Because the collected data can be analyzed in real time, optimizing plant operations can be optimized, predicting maintenance schedules for mechanical facilities or quickly replacing equipment with faulty ones. In addition, various information needed for efficient operation can be obtained, such as improving the quality of the products produced. Using 5G wireless network and fog node and cloud computing, this paper introduces a new platform that supports efficient analysis of big data collected in smart factories. Leveraging various resources of 5G wireless network, it provides an optimized environment for collecting IoT data such as size, speed, delay and variety. It also provides big data analytic services through fog nodes and cloud computing and addresses various requirements for data collection, processing, analysis and management. This paper describes the requirements and design components of the proposed platform. Introduce case studies using data sets obtained from smart factories to validate the platform and provide meaningful results. The experimental results clearly show the benefits and practicalities of the platform.",

keywords = "5G-networked Smart Factory, Big data, Cloud computing, Fog computing, Industrial IoT",

author = "Yohan Han and Byungjun Park and Jongpil Jeong",

note = "Publisher Copyright: {\textcopyright} 2019, Springer Nature Switzerland AG.; 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference date: 01-07-2019 Through 04-07-2019",

year = "2019",

doi = "10.1007/978-3-030-24296-1\_5",

language = "English",

isbn = "9783030242954",

series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",

publisher = "Springer Verlag",

pages = "44--52",

editor = "Sanjay Misra and Osvaldo Gervasi and Beniamino Murgante and Elena Stankova and Vladimir Korkhov and Carmelo Torre and Eufemia Tarantino and Rocha, \{Ana Maria A.C.\} and David Taniar and Apduhan, \{Bernady O.\}",

booktitle = "Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings",

}

Han, Y, Park, B & Jeong, J 2019, Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory. in S Misra, O Gervasi, B Murgante, E Stankova, V Korkhov, C Torre, E Tarantino, AMAC Rocha, D Taniar & BO Apduhan (eds), Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 11620 LNCS, Springer Verlag, pp. 44-52, 19th International Conference on Computational Science and Its Applications, ICCSA 2019, Saint Petersburg, Russian Federation, 1/07/19. https://doi.org/10.1007/978-3-030-24296-1_5

Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory. / Han, Yohan; Park, Byungjun; Jeong, Jongpil.
Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. ed. / Sanjay Misra; Osvaldo Gervasi; Beniamino Murgante; Elena Stankova; Vladimir Korkhov; Carmelo Torre; Eufemia Tarantino; Ana Maria A.C. Rocha; David Taniar; Bernady O. Apduhan. Springer Verlag, 2019. p. 44-52 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11620 LNCS).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory

AU - Han, Yohan

AU - Park, Byungjun

AU - Jeong, Jongpil

PY - 2019

Y1 - 2019

N2 - Industrial IoT data analysis is an essential means of obtaining important information in efficient smart factory operation. IoT devices connected to Smart Factory produce large amount of data from variety of mechanical facilities that actually operate. Because the collected data can be analyzed in real time, optimizing plant operations can be optimized, predicting maintenance schedules for mechanical facilities or quickly replacing equipment with faulty ones. In addition, various information needed for efficient operation can be obtained, such as improving the quality of the products produced. Using 5G wireless network and fog node and cloud computing, this paper introduces a new platform that supports efficient analysis of big data collected in smart factories. Leveraging various resources of 5G wireless network, it provides an optimized environment for collecting IoT data such as size, speed, delay and variety. It also provides big data analytic services through fog nodes and cloud computing and addresses various requirements for data collection, processing, analysis and management. This paper describes the requirements and design components of the proposed platform. Introduce case studies using data sets obtained from smart factories to validate the platform and provide meaningful results. The experimental results clearly show the benefits and practicalities of the platform.

AB - Industrial IoT data analysis is an essential means of obtaining important information in efficient smart factory operation. IoT devices connected to Smart Factory produce large amount of data from variety of mechanical facilities that actually operate. Because the collected data can be analyzed in real time, optimizing plant operations can be optimized, predicting maintenance schedules for mechanical facilities or quickly replacing equipment with faulty ones. In addition, various information needed for efficient operation can be obtained, such as improving the quality of the products produced. Using 5G wireless network and fog node and cloud computing, this paper introduces a new platform that supports efficient analysis of big data collected in smart factories. Leveraging various resources of 5G wireless network, it provides an optimized environment for collecting IoT data such as size, speed, delay and variety. It also provides big data analytic services through fog nodes and cloud computing and addresses various requirements for data collection, processing, analysis and management. This paper describes the requirements and design components of the proposed platform. Introduce case studies using data sets obtained from smart factories to validate the platform and provide meaningful results. The experimental results clearly show the benefits and practicalities of the platform.

KW - 5G-networked Smart Factory

KW - Big data

KW - Cloud computing

KW - Fog computing

KW - Industrial IoT

UR - https://www.scopus.com/pages/publications/85069215838

U2 - 10.1007/978-3-030-24296-1_5

DO - 10.1007/978-3-030-24296-1_5

M3 - Conference contribution

AN - SCOPUS:85069215838

SN - 9783030242954

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 44

EP - 52

BT - Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings

A2 - Misra, Sanjay

A2 - Gervasi, Osvaldo

A2 - Murgante, Beniamino

A2 - Stankova, Elena

A2 - Korkhov, Vladimir

A2 - Torre, Carmelo

A2 - Tarantino, Eufemia

A2 - Rocha, Ana Maria A.C.

A2 - Taniar, David

A2 - Apduhan, Bernady O.

PB - Springer Verlag

T2 - 19th International Conference on Computational Science and Its Applications, ICCSA 2019

Y2 - 1 July 2019 through 4 July 2019

ER -

Han Y, Park B, Jeong J. Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory. In Misra S, Gervasi O, Murgante B, Stankova E, Korkhov V, Torre C, Tarantino E, Rocha AMAC, Taniar D, Apduhan BO, editors, Computational Science and Its Applications – ICCSA 2019 - 19th International Conference, 2019, Proceedings. Springer Verlag. 2019. p. 44-52. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-030-24296-1_5

Fog Based IIoT Architecture Based on Big Data Analytics for 5G-networked Smart Factory

Abstract

Publication series

Conference

UN SDGs

Keywords

Access to Document

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