Two-Level Allocation for H-CRAN Architecture Based in Offloading
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742019000200141 |
Resumo: | Abstract The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the TLA (Two-Level Allocation) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Signal-to-noise ratio) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling better service to the users. |
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Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
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Two-Level Allocation for H-CRAN Architecture Based in OffloadingMobile Networks5GH-CRANQoSOffloadingTLAAbstract The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the TLA (Two-Level Allocation) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Signal-to-noise ratio) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling better service to the users.Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo2019-06-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742019000200141Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.18 n.2 2019reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applicationsinstname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)instacron:SBMO10.1590/2179-10742019v18i21484info:eu-repo/semantics/openAccessGonçalves,Mariane de Paula da SilvaLeto,Matheus BarrosVieira,Rafael FogarolliBarros,Fabrício José BritoCardoso,Diego Lisboaeng2019-06-17T00:00:00Zoai:scielo:S2179-10742019000200141Revistahttp://www.jmoe.org/index.php/jmoe/indexONGhttps://old.scielo.br/oai/scielo-oai.php||editor_jmoe@sbmo.org.br2179-10742179-1074opendoar:2019-06-17T00:00Journal of Microwaves. Optoelectronics and Electromagnetic Applications - Sociedade Brasileira de Microondas e Optoeletrônica (SBMO)false |
dc.title.none.fl_str_mv |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
title |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
spellingShingle |
Two-Level Allocation for H-CRAN Architecture Based in Offloading Gonçalves,Mariane de Paula da Silva Mobile Networks 5G H-CRAN QoS Offloading TLA |
title_short |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
title_full |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
title_fullStr |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
title_full_unstemmed |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
title_sort |
Two-Level Allocation for H-CRAN Architecture Based in Offloading |
author |
Gonçalves,Mariane de Paula da Silva |
author_facet |
Gonçalves,Mariane de Paula da Silva Leto,Matheus Barros Vieira,Rafael Fogarolli Barros,Fabrício José Brito Cardoso,Diego Lisboa |
author_role |
author |
author2 |
Leto,Matheus Barros Vieira,Rafael Fogarolli Barros,Fabrício José Brito Cardoso,Diego Lisboa |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Gonçalves,Mariane de Paula da Silva Leto,Matheus Barros Vieira,Rafael Fogarolli Barros,Fabrício José Brito Cardoso,Diego Lisboa |
dc.subject.por.fl_str_mv |
Mobile Networks 5G H-CRAN QoS Offloading TLA |
topic |
Mobile Networks 5G H-CRAN QoS Offloading TLA |
description |
Abstract The accelerated data and apps growth represents significant challenges to the next generation of mobile networks. Amongst them, it is highlighted the necessity for a co-existence of new and old patterns during the transition of architectures. Thus, this paper has investigated solutions for offloading into a hybrid architecture, also known as H-CRAN (Heterogeneous Cloud Radio Access Network Architecture), that centralizes processing and searches a better use of the network resources. The strategy of optimization was analyzed through the evolutive algorithm PSO (Particle Swarm Optimization), in order to find a suboptimal solution to the TLA (Two-Level Allocation) in the H-CRAN architecture and another one based on FIFO (First In, First Out), for benchmarking purposes. SNR (Signal-to-noise ratio) average, Maximum Bit Rate, the number of users with or without connections and number of connections in RRHs and macro were used as performance measurements. Through the results, it was noticed an improvement of approximately 60% in the Maximum Bit Rate when compared to the traditional approach, enabling better service to the users. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-06-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742019000200141 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S2179-10742019000200141 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/2179-10742019v18i21484 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo |
publisher.none.fl_str_mv |
Sociedade Brasileira de Microondas e Optoeletrônica e Sociedade Brasileira de Eletromagnetismo |
dc.source.none.fl_str_mv |
Journal of Microwaves, Optoelectronics and Electromagnetic Applications v.18 n.2 2019 reponame:Journal of Microwaves. Optoelectronics and Electromagnetic Applications instname:Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) instacron:SBMO |
instname_str |
Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) |
instacron_str |
SBMO |
institution |
SBMO |
reponame_str |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
collection |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications |
repository.name.fl_str_mv |
Journal of Microwaves. Optoelectronics and Electromagnetic Applications - Sociedade Brasileira de Microondas e Optoeletrônica (SBMO) |
repository.mail.fl_str_mv |
||editor_jmoe@sbmo.org.br |
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1752122126613086208 |