Reliable: Resource allocation mechanism for 5G network using mobile edge computing
Autor(a) principal: | |
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Data de Publicação: | 2020 |
Outros Autores: | , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UNESP |
Texto Completo: | http://dx.doi.org/10.3390/s20195449 http://hdl.handle.net/11449/206552 |
Resumo: | Technological advancement is currently focused on the miniaturization of devices, and integrated circuits allow us to observe the increase in the number of Internet of Things (IoT) devices. Most IoT services and devices require an Internet connection, which needs to provide the minimum processing, storage and networking requirements to best serve a requested service. One of the main goals of 5G networks is to comply with the user’s various Quality of Service (QoS) requirements in different application scenarios. Fifth-generation networks use Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) concepts to achieve these QoS requirements. However, the computational resource allocation mechanisms required by the services are considered very complex. Thus, in this paper, we propose an allocation and management resources mechanism for 5G networks that uses MEC and simple mathematical methods to reduce the model complexity. The mechanism decides to allocate the resource in MEC to meet the requirements requested by the user. The simulation results show that the proposed mechanism provides a larger amount of services, leading to a reduction in the service lock number and as a reduction in the blocking ratio of services due to the accuracy of the approach and its load balancing in the process of resource allocation. |
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Repositório Institucional da UNESP |
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Reliable: Resource allocation mechanism for 5G network using mobile edge computing5GMECResource allocationTechnological advancement is currently focused on the miniaturization of devices, and integrated circuits allow us to observe the increase in the number of Internet of Things (IoT) devices. Most IoT services and devices require an Internet connection, which needs to provide the minimum processing, storage and networking requirements to best serve a requested service. One of the main goals of 5G networks is to comply with the user’s various Quality of Service (QoS) requirements in different application scenarios. Fifth-generation networks use Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) concepts to achieve these QoS requirements. However, the computational resource allocation mechanisms required by the services are considered very complex. Thus, in this paper, we propose an allocation and management resources mechanism for 5G networks that uses MEC and simple mathematical methods to reduce the model complexity. The mechanism decides to allocate the resource in MEC to meet the requirements requested by the user. The simulation results show that the proposed mechanism provides a larger amount of services, leading to a reduction in the service lock number and as a reduction in the blocking ratio of services due to the accuracy of the approach and its load balancing in the process of resource allocation.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)Computer System Department São Paulo State University (UNESP), Campus São José do Rio PretoInstitute of Mathematical and Computer Sciences University of São Paulo (USP)Computer Science Department Federal University of São Carlos (UFSCAR)Institute of Computing University of Campinas (UNICAMP)Computer Science Faculty Federal University of Pará (UFPA)Computer System Department São Paulo State University (UNESP), Campus São José do Rio PretoCNPq: 309822/2018-1CNPq: 407248/2018-8Universidade Estadual Paulista (Unesp)Universidade de São Paulo (USP)Universidade Federal de São Carlos (UFSCar)Universidade Estadual de Campinas (UNICAMP)Universidade Federal do Pará (UFPA)Pereira, Rickson S. [UNESP]Lieira, Douglas D. [UNESP]da Silva, Marco A. C.Pimenta, Adinovam H. M.da Costa, Joahannes B. D.Rosário, DenisVillas, LeandroMeneguette, Rodolfo I.2021-06-25T10:34:10Z2021-06-25T10:34:10Z2020-10-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/article1-18http://dx.doi.org/10.3390/s20195449Sensors (Switzerland), v. 20, n. 19, p. 1-18, 2020.1424-8220http://hdl.handle.net/11449/20655210.3390/s201954492-s2.0-85091408252Scopusreponame:Repositório Institucional da UNESPinstname:Universidade Estadual Paulista (UNESP)instacron:UNESPengSensors (Switzerland)info:eu-repo/semantics/openAccess2021-10-23T07:27:32Zoai:repositorio.unesp.br:11449/206552Repositório InstitucionalPUBhttp://repositorio.unesp.br/oai/requestopendoar:29462024-08-05T14:03:45.251482Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP)false |
dc.title.none.fl_str_mv |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
title |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
spellingShingle |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing Pereira, Rickson S. [UNESP] 5G MEC Resource allocation |
title_short |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
title_full |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
title_fullStr |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
title_full_unstemmed |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
title_sort |
Reliable: Resource allocation mechanism for 5G network using mobile edge computing |
author |
Pereira, Rickson S. [UNESP] |
author_facet |
Pereira, Rickson S. [UNESP] Lieira, Douglas D. [UNESP] da Silva, Marco A. C. Pimenta, Adinovam H. M. da Costa, Joahannes B. D. Rosário, Denis Villas, Leandro Meneguette, Rodolfo I. |
author_role |
author |
author2 |
Lieira, Douglas D. [UNESP] da Silva, Marco A. C. Pimenta, Adinovam H. M. da Costa, Joahannes B. D. Rosário, Denis Villas, Leandro Meneguette, Rodolfo I. |
author2_role |
author author author author author author author |
dc.contributor.none.fl_str_mv |
Universidade Estadual Paulista (Unesp) Universidade de São Paulo (USP) Universidade Federal de São Carlos (UFSCar) Universidade Estadual de Campinas (UNICAMP) Universidade Federal do Pará (UFPA) |
dc.contributor.author.fl_str_mv |
Pereira, Rickson S. [UNESP] Lieira, Douglas D. [UNESP] da Silva, Marco A. C. Pimenta, Adinovam H. M. da Costa, Joahannes B. D. Rosário, Denis Villas, Leandro Meneguette, Rodolfo I. |
dc.subject.por.fl_str_mv |
5G MEC Resource allocation |
topic |
5G MEC Resource allocation |
description |
Technological advancement is currently focused on the miniaturization of devices, and integrated circuits allow us to observe the increase in the number of Internet of Things (IoT) devices. Most IoT services and devices require an Internet connection, which needs to provide the minimum processing, storage and networking requirements to best serve a requested service. One of the main goals of 5G networks is to comply with the user’s various Quality of Service (QoS) requirements in different application scenarios. Fifth-generation networks use Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) concepts to achieve these QoS requirements. However, the computational resource allocation mechanisms required by the services are considered very complex. Thus, in this paper, we propose an allocation and management resources mechanism for 5G networks that uses MEC and simple mathematical methods to reduce the model complexity. The mechanism decides to allocate the resource in MEC to meet the requirements requested by the user. The simulation results show that the proposed mechanism provides a larger amount of services, leading to a reduction in the service lock number and as a reduction in the blocking ratio of services due to the accuracy of the approach and its load balancing in the process of resource allocation. |
publishDate |
2020 |
dc.date.none.fl_str_mv |
2020-10-01 2021-06-25T10:34:10Z 2021-06-25T10:34:10Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://dx.doi.org/10.3390/s20195449 Sensors (Switzerland), v. 20, n. 19, p. 1-18, 2020. 1424-8220 http://hdl.handle.net/11449/206552 10.3390/s20195449 2-s2.0-85091408252 |
url |
http://dx.doi.org/10.3390/s20195449 http://hdl.handle.net/11449/206552 |
identifier_str_mv |
Sensors (Switzerland), v. 20, n. 19, p. 1-18, 2020. 1424-8220 10.3390/s20195449 2-s2.0-85091408252 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Sensors (Switzerland) |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
1-18 |
dc.source.none.fl_str_mv |
Scopus reponame:Repositório Institucional da UNESP instname:Universidade Estadual Paulista (UNESP) instacron:UNESP |
instname_str |
Universidade Estadual Paulista (UNESP) |
instacron_str |
UNESP |
institution |
UNESP |
reponame_str |
Repositório Institucional da UNESP |
collection |
Repositório Institucional da UNESP |
repository.name.fl_str_mv |
Repositório Institucional da UNESP - Universidade Estadual Paulista (UNESP) |
repository.mail.fl_str_mv |
|
_version_ |
1808128310245326848 |