A Framework of Fog Computing: Architecture, Challenges, and Optimization

Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially...
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Autor*in:	Yang Liu [verfasserIn] Jonathan E. Fieldsend [verfasserIn] Geyong Min [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2017

Schlagwörter:	Fog computing genetic algorithms Internet of Things optimization

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 5(2017), Seite 25445-25454
Übergeordnetes Werk:	volume:5 ; year:2017 ; pages:25445-25454

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2017.2766923

Katalog-ID:	DOAJ068436858

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spelling	10.1109/ACCESS.2017.2766923 doi (DE-627)DOAJ068436858 (DE-599)DOAJaaf1e87105b44d46a896ad515f58ce74 DE-627 ger DE-627 rakwb eng TK1-9971 Yang Liu verfasserin aut A Framework of Fog Computing: Architecture, Challenges, and Optimization 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this paper. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a genetic algorithm. The resulting analysis generates some important insights on the scalability of the FC systems. Fog computing genetic algorithms Internet of Things optimization Electrical engineering. Electronics. Nuclear engineering Jonathan E. Fieldsend verfasserin aut Geyong Min verfasserin aut In IEEE Access IEEE, 2014 5(2017), Seite 25445-25454 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:5 year:2017 pages:25445-25454 https://doi.org/10.1109/ACCESS.2017.2766923 kostenfrei https://doaj.org/article/aaf1e87105b44d46a896ad515f58ce74 kostenfrei https://ieeexplore.ieee.org/document/8085127/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2017 25445-25454
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allfieldsSound	10.1109/ACCESS.2017.2766923 doi (DE-627)DOAJ068436858 (DE-599)DOAJaaf1e87105b44d46a896ad515f58ce74 DE-627 ger DE-627 rakwb eng TK1-9971 Yang Liu verfasserin aut A Framework of Fog Computing: Architecture, Challenges, and Optimization 2017 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this paper. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a genetic algorithm. The resulting analysis generates some important insights on the scalability of the FC systems. Fog computing genetic algorithms Internet of Things optimization Electrical engineering. Electronics. Nuclear engineering Jonathan E. Fieldsend verfasserin aut Geyong Min verfasserin aut In IEEE Access IEEE, 2014 5(2017), Seite 25445-25454 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:5 year:2017 pages:25445-25454 https://doi.org/10.1109/ACCESS.2017.2766923 kostenfrei https://doaj.org/article/aaf1e87105b44d46a896ad515f58ce74 kostenfrei https://ieeexplore.ieee.org/document/8085127/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 5 2017 25445-25454
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callnumber-first	T - Technology
author	Yang Liu
spellingShingle	Yang Liu misc TK1-9971 misc Fog computing misc genetic algorithms misc Internet of Things misc optimization misc Electrical engineering. Electronics. Nuclear engineering A Framework of Fog Computing: Architecture, Challenges, and Optimization
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topic_title	TK1-9971 A Framework of Fog Computing: Architecture, Challenges, and Optimization Fog computing genetic algorithms Internet of Things optimization
topic	misc TK1-9971 misc Fog computing misc genetic algorithms misc Internet of Things misc optimization misc Electrical engineering. Electronics. Nuclear engineering
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title	A Framework of Fog Computing: Architecture, Challenges, and Optimization
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title_auth	A Framework of Fog Computing: Architecture, Challenges, and Optimization
abstract	Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this paper. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a genetic algorithm. The resulting analysis generates some important insights on the scalability of the FC systems.
abstractGer	Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this paper. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a genetic algorithm. The resulting analysis generates some important insights on the scalability of the FC systems.
abstract_unstemmed	Fog computing (FC) is an emerging distributed computing platform aimed at bringing computation close to its data sources, which can reduce the latency and cost of delivering data to a remote cloud. This feature and related advantages are desirable for many Internet-of-Things applications, especially latency sensitive and mission intensive services. With comparisons to other computing technologies, the definition and architecture of FC are presented in this paper. The framework of resource allocation for latency reduction combined with reliability, fault tolerance, privacy, and underlying optimization problems are also discussed. We then investigate an application scenario and conduct resource optimization by formulating the optimization problem and solving it via a genetic algorithm. The resulting analysis generates some important insights on the scalability of the FC systems.
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title_short	A Framework of Fog Computing: Architecture, Challenges, and Optimization
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