Publicação:
TRIAD: Whale Optimization Algorithm for 5G-IoT Resource Allocation Decision in Edge Computing

dc.contributor.authorLieira, Douglas Dias [UNESP]
dc.contributor.authorQuessada, Matheus Sanches [UNESP]
dc.contributor.authorCristiani, Andre Luis
dc.contributor.authorImmich, Roger
dc.contributor.authorMeneguette, Rodolfo Ipolito
dc.contributor.authorRocha, A.
dc.contributor.authorGoncalves, R.
dc.contributor.authorPenalvo, F. G.
dc.contributor.authorMartins, J.
dc.contributor.institutionUniversidade Estadual Paulista (UNESP)
dc.contributor.institutionInst Fed Sao Paulo IFSP Catanduva
dc.contributor.institutionUniversidade Federal de São Carlos (UFSCar)
dc.contributor.institutionUniv Fed Rio Grande do Norte UFRN
dc.contributor.institutionUniversidade de São Paulo (USP)
dc.date.accessioned2022-11-30T13:44:55Z
dc.date.available2022-11-30T13:44:55Z
dc.date.issued2021-01-01
dc.description.abstractThe massive growth in the number of 5G-IoT devices circulating in the world has increased the demand for computing resources in recent years. That way, it is necessary to search for the development of new solutions or improvements to existing ones. Edge computing is one of the solutions that have been used to improve the care of these types of devices. In this work, we proposed a mechanism that uses the whale optimization algorithm for 5G-IoT resource allocation decision in edge computing (TRIAD). The TRIAD was compared with the Greedy and Reliable techniques, available in the literature. The results show that the proposed algorithm had excellent efficiency in the service of the devices, in addition to denying fewer requests and blocking fewer devices during the search. The TRIAD, in some situations of the simulation, served approximately 265% more services, denied 56% less requests and blocked 65% less services.en
dc.description.affiliationUniv Estadual Paulista UNESP, DCCE, Sao Jose Do Rio Preto, SP, Brazil
dc.description.affiliationInst Fed Sao Paulo IFSP Catanduva, Sao Jose Do Rio Preto, SP, Brazil
dc.description.affiliationUniv Fed Sao Carlos UFSCar, Dept Comp, Sao Carlos, SP, Brazil
dc.description.affiliationUniv Fed Rio Grande do Norte UFRN, Inst Metropole Digital, Natal, RN, Brazil
dc.description.affiliationUniv Sao Paulo, Dept Sistemas Comp ICMC, Sao Carlos, SP, Brazil
dc.description.affiliationUnespUniv Estadual Paulista UNESP, DCCE, Sao Jose Do Rio Preto, SP, Brazil
dc.format.extent6
dc.identifier.citationProceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021). New York: Ieee, 6 p., 2021.
dc.identifier.issn2166-0727
dc.identifier.urihttp://hdl.handle.net/11449/237785
dc.identifier.wosWOS:000824588500306
dc.language.isopor
dc.publisherIeee
dc.relation.ispartofProceedings Of 2021 16th Iberian Conference On Information Systems And Technologies (cisti'2021)
dc.sourceWeb of Science
dc.subjectEdge computing
dc.subjectInternet of things
dc.subjectMeta-heuristic
dc.subjectResource allocation
dc.subjectWhale optimization algorithm
dc.titleTRIAD: Whale Optimization Algorithm for 5G-IoT Resource Allocation Decision in Edge Computingen
dc.typeTrabalho apresentado em evento
dcterms.licensehttp://www.ieee.org/publications_standards/publications/rights/rights_policies.html
dcterms.rightsHolderIeee
dspace.entity.typePublication
unesp.campusUniversidade Estadual Paulista (UNESP), Instituto de Biociências Letras e Ciências Exatas, São José do Rio Pretopt
unesp.departmentCiências da Computação e Estatística - IBILCEpt

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