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    Rights statement: This is the peer reviewed version of the following article: Giang, NK, Lea, R, Leung, VCM. Developing applications in large scale, dynamic fog computing: A case study. Software: Practice and Experience 2020; 50: 519– 532 https://doi.org/10.1002/spe.2695 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/spe.2695 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

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Developing applications in large scale, dynamic fog computing: A case study

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Developing applications in large scale, dynamic fog computing: A case study. / Giang, N.K.; Lea, R.; Leung, V.C.M.
In: Software: Practice and Experience, Vol. 50, No. 5, 01.05.2020, p. 519-532.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Harvard

Giang, NK, Lea, R & Leung, VCM 2020, 'Developing applications in large scale, dynamic fog computing: A case study', Software: Practice and Experience, vol. 50, no. 5, pp. 519-532. https://doi.org/10.1002/spe.2695

APA

Giang, N. K., Lea, R., & Leung, V. C. M. (2020). Developing applications in large scale, dynamic fog computing: A case study. Software: Practice and Experience, 50(5), 519-532. https://doi.org/10.1002/spe.2695

Vancouver

Giang NK, Lea R, Leung VCM. Developing applications in large scale, dynamic fog computing: A case study. Software: Practice and Experience. 2020 May 1;50(5):519-532. Epub 2019 Apr 21. doi: 10.1002/spe.2695

Author

Giang, N.K. ; Lea, R. ; Leung, V.C.M. / Developing applications in large scale, dynamic fog computing : A case study. In: Software: Practice and Experience. 2020 ; Vol. 50, No. 5. pp. 519-532.

Bibtex

@article{d7eb982e8a724a2baf8c0f5a3467c49f,
title = "Developing applications in large scale, dynamic fog computing: A case study",
abstract = "In recent years, fog computing has emerged as a new distributed system model for a large class of applications that are data-intensive or delay-sensitive. By exploiting widely distributed computing infrastructure that is located closer to the network edge, communication cost and service response time can be significantly reduced. However, developing this class of applications is not straightforward and requires addressing three key challenges, ie, supporting the dynamic nature of the edge network, managing the context-dependent characteristics of application logic, and dealing with the large scale of the system. In this paper, we present a case study in building fog computing applications using our open source platform Distributed Node-RED (DNR). In particular, we show how applications can be decomposed and deployed to a geographically distributed infrastructure using DNR, and how existing software components can be adapted and reused to participate in fog applications. We present a lab-based implementation of a fog application built using DNR that addresses the first two of the issues highlighted earlier. To validate that our approach also deals with large scale, we augment our live trial with a large scale simulation of the application model, conducted in Omnet++, which shows the scalability of the model and how it supports the dynamic nature of fog applications. {\textcopyright} 2019 John Wiley & Sons, Ltd.",
keywords = "coordination, dataflow, dynamic, edge/fog computing, exogenous, large scale, Application programs, Computation theory, Dynamics, Fog, Open source software, Open systems, Dataflow, Fog computing",
author = "N.K. Giang and R. Lea and V.C.M. Leung",
note = "This is the peer reviewed version of the following article: Giang, NK, Lea, R, Leung, VCM. Developing applications in large scale, dynamic fog computing: A case study. Softw: Pract Exper. 2019; 1– 14. https://doi.org/10.1002/spe.2695 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/spe.2695 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving. ",
year = "2020",
month = may,
day = "1",
doi = "10.1002/spe.2695",
language = "English",
volume = "50",
pages = "519--532",
journal = "Software: Practice and Experience",
issn = "0038-0644",
publisher = "John Wiley and Sons Ltd",
number = "5",

}

RIS

TY - JOUR

T1 - Developing applications in large scale, dynamic fog computing

T2 - A case study

AU - Giang, N.K.

AU - Lea, R.

AU - Leung, V.C.M.

N1 - This is the peer reviewed version of the following article: Giang, NK, Lea, R, Leung, VCM. Developing applications in large scale, dynamic fog computing: A case study. Softw: Pract Exper. 2019; 1– 14. https://doi.org/10.1002/spe.2695 which has been published in final form at https://onlinelibrary.wiley.com/doi/full/10.1002/spe.2695 This article may be used for non-commercial purposes in accordance With Wiley Terms and Conditions for self-archiving.

PY - 2020/5/1

Y1 - 2020/5/1

N2 - In recent years, fog computing has emerged as a new distributed system model for a large class of applications that are data-intensive or delay-sensitive. By exploiting widely distributed computing infrastructure that is located closer to the network edge, communication cost and service response time can be significantly reduced. However, developing this class of applications is not straightforward and requires addressing three key challenges, ie, supporting the dynamic nature of the edge network, managing the context-dependent characteristics of application logic, and dealing with the large scale of the system. In this paper, we present a case study in building fog computing applications using our open source platform Distributed Node-RED (DNR). In particular, we show how applications can be decomposed and deployed to a geographically distributed infrastructure using DNR, and how existing software components can be adapted and reused to participate in fog applications. We present a lab-based implementation of a fog application built using DNR that addresses the first two of the issues highlighted earlier. To validate that our approach also deals with large scale, we augment our live trial with a large scale simulation of the application model, conducted in Omnet++, which shows the scalability of the model and how it supports the dynamic nature of fog applications. © 2019 John Wiley & Sons, Ltd.

AB - In recent years, fog computing has emerged as a new distributed system model for a large class of applications that are data-intensive or delay-sensitive. By exploiting widely distributed computing infrastructure that is located closer to the network edge, communication cost and service response time can be significantly reduced. However, developing this class of applications is not straightforward and requires addressing three key challenges, ie, supporting the dynamic nature of the edge network, managing the context-dependent characteristics of application logic, and dealing with the large scale of the system. In this paper, we present a case study in building fog computing applications using our open source platform Distributed Node-RED (DNR). In particular, we show how applications can be decomposed and deployed to a geographically distributed infrastructure using DNR, and how existing software components can be adapted and reused to participate in fog applications. We present a lab-based implementation of a fog application built using DNR that addresses the first two of the issues highlighted earlier. To validate that our approach also deals with large scale, we augment our live trial with a large scale simulation of the application model, conducted in Omnet++, which shows the scalability of the model and how it supports the dynamic nature of fog applications. © 2019 John Wiley & Sons, Ltd.

KW - coordination

KW - dataflow

KW - dynamic

KW - edge/fog computing

KW - exogenous

KW - large scale

KW - Application programs

KW - Computation theory

KW - Dynamics

KW - Fog

KW - Open source software

KW - Open systems

KW - Dataflow

KW - Fog computing

U2 - 10.1002/spe.2695

DO - 10.1002/spe.2695

M3 - Journal article

VL - 50

SP - 519

EP - 532

JO - Software: Practice and Experience

JF - Software: Practice and Experience

SN - 0038-0644

IS - 5

ER -