Sustainable Service Allocation Using a Metaheuristic Technique in a Fog Server for Industrial Applications

Mishra, SK; Puthal, D; Rodrigues, JJPC; Sahoo, B; Dutkiewicz, E

Sustainable Service Allocation Using a Metaheuristic Technique in a Fog Server for Industrial Applications

Mishra, SK Puthal, D

Rodrigues, JJPC Sahoo, B Dutkiewicz, E

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Publication Type:: Journal Article
Citation:: IEEE Transactions on Industrial Informatics, 2018, 14 (10), pp. 4497 - 4506
Issue Date:: 2018-10-01

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Field	Value	Language
dc.contributor.author	Mishra, SK	en_US
dc.contributor.author	Puthal, D https://orcid.org/0000-0002-8332-278X	en_US
dc.contributor.author	Rodrigues, JJPC	en_US
dc.contributor.author	Sahoo, B	en_US
dc.contributor.author	Dutkiewicz, E https://orcid.org/0000-0002-4268-9286	en_US
dc.date.issued	2018-10-01	en_US
dc.identifier.citation	IEEE Transactions on Industrial Informatics, 2018, 14 (10), pp. 4497 - 4506	en_US
dc.identifier.issn	1551-3203	en_US
dc.identifier.uri	http://hdl.handle.net/10453/129742
dc.description.abstract	© 2005-2012 IEEE. Reducing energy consumption in the fog computing environment is both a research and an operational challenge for the current research community and industry. There are several industries such as finance industry or healthcare industry that require a rich resource platform to process big data along with edge computing in fog architecture. As a result, sustainable computing in a fog server plays a key role in fog computing hierarchy. The energy consumption in fog servers depends on the allocation techniques of services (user requests) to a set of virtual machines (VMs). This service request allocation in a fog computing environment is a nondeterministic polynomial-time hard problem. In this paper, the scheduling of service requests to VMs is presented as a bi-objective minimization problem, where a tradeoff is maintained between the energy consumption and makespan. Specifically, this paper proposes a metaheuristic-based service allocation framework using three metaheuristic techniques, such as particle swarm optimization (PSO), binary PSO, and bat algorithm. These proposed techniques allow us to deal with the heterogeneity of resources in the fog computing environment. This paper has validated the performance of these metaheuristic-based service allocation algorithms by conducting a set of rigorous evaluations.	en_US
dc.relation.ispartof	IEEE Transactions on Industrial Informatics	en_US
dc.relation.isbasedon	10.1109/TII.2018.2791619	en_US
dc.rights	info:eu-repo/semantics/closedAccess
dc.subject.classification	Electrical & Electronic Engineering	en_US
dc.title	Sustainable Service Allocation Using a Metaheuristic Technique in a Fog Server for Industrial Applications	en_US
dc.type	Journal Article
utslib.citation.volume	10	en_US
utslib.citation.volume	14	en_US
utslib.for	0906 Electrical and Electronic Engineering	en_US
utslib.for	0801 Artificial Intelligence and Image Processing	en_US
utslib.for	08 Information and Computing Sciences	en_US
utslib.for	09 Engineering	en_US
utslib.for	10 Technology	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Electrical and Data Engineering
pubs.organisational-group	/University of Technology Sydney/Faculty of Engineering and Information Technology/School of Information, Systems and Modelling
pubs.organisational-group	/University of Technology Sydney/Strength - GBDTC - Global Big Data Technologies
utslib.copyright.status	closed_access	*
pubs.issue	10	en_US
pubs.publication-status	Published	en_US
pubs.volume	14	en_US

Abstract:

© 2005-2012 IEEE. Reducing energy consumption in the fog computing environment is both a research and an operational challenge for the current research community and industry. There are several industries such as finance industry or healthcare industry that require a rich resource platform to process big data along with edge computing in fog architecture. As a result, sustainable computing in a fog server plays a key role in fog computing hierarchy. The energy consumption in fog servers depends on the allocation techniques of services (user requests) to a set of virtual machines (VMs). This service request allocation in a fog computing environment is a nondeterministic polynomial-time hard problem. In this paper, the scheduling of service requests to VMs is presented as a bi-objective minimization problem, where a tradeoff is maintained between the energy consumption and makespan. Specifically, this paper proposes a metaheuristic-based service allocation framework using three metaheuristic techniques, such as particle swarm optimization (PSO), binary PSO, and bat algorithm. These proposed techniques allow us to deal with the heterogeneity of resources in the fog computing environment. This paper has validated the performance of these metaheuristic-based service allocation algorithms by conducting a set of rigorous evaluations.

Please use this identifier to cite or link to this item:

http://hdl.handle.net/10453/129742