Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks
Autor(a) principal: | |
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Data de Publicação: | 2023 |
Outros Autores: | , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10773/39947 |
Resumo: | Multiaccess edge computing (MEC) service migration is a technology whose key objective is to support ultralow-latency access to services. However, the complex ultralarge-scale edge service migration problem requires extensive research efforts, regarding the foreseen ultradensified edge nodes in 5G and beyond. In this article, we propose a novel dynamic service migration optimization architecture for ultralarge-scale MEC networks. We develop a new multicriteria decision-making algorithm: Technique for order of preference by similarity to ideal solution with attribute-based Niche count, named TOPANSIS, which showcases its strength to provide an optimal solution for service migration in large-scale deployments towards optimal data rate, latency, and load balancing. We further decentralize the operation of TOPANSIS to release the traffic burden from central datacenters by leveraging local decision making by edge nodes, while relying on central cloud coordination to account for the overall network information. Simulation results showcase that the proposed architecture outperforms the selected benchmarks with an average improvement of 39.41% for latency, 2.92% for data rate, as well as 10.53% and 6.26% for RAM and CPU load balancing, respectively. Moreover, the feasibility of the proposed solution is validated by means of a proof-of-concept implementation and experimental assessments. |
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Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing NetworksEdge computingMulticriteria decision making (MCDM)Resource allocationService migrationMultiaccess edge computing (MEC) service migration is a technology whose key objective is to support ultralow-latency access to services. However, the complex ultralarge-scale edge service migration problem requires extensive research efforts, regarding the foreseen ultradensified edge nodes in 5G and beyond. In this article, we propose a novel dynamic service migration optimization architecture for ultralarge-scale MEC networks. We develop a new multicriteria decision-making algorithm: Technique for order of preference by similarity to ideal solution with attribute-based Niche count, named TOPANSIS, which showcases its strength to provide an optimal solution for service migration in large-scale deployments towards optimal data rate, latency, and load balancing. We further decentralize the operation of TOPANSIS to release the traffic burden from central datacenters by leveraging local decision making by edge nodes, while relying on central cloud coordination to account for the overall network information. Simulation results showcase that the proposed architecture outperforms the selected benchmarks with an average improvement of 39.41% for latency, 2.92% for data rate, as well as 10.53% and 6.26% for RAM and CPU load balancing, respectively. Moreover, the feasibility of the proposed solution is validated by means of a proof-of-concept implementation and experimental assessments.IEEE2026-01-01T00:00:00Z2023-11-01T00:00:00Z2023-11-01info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10773/39947eng1551-320310.1109/TII.2023.3244321Chi, Hao RanSilva, RuiSantos, DavidQuevedo, JoséCorujo, DanielAbboud, OsamaRadwan, AymanHecker, ArturAguiar, Rui L.info:eu-repo/semantics/embargoedAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-02-22T12:17:55Zoai:ria.ua.pt:10773/39947Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T03:09:57.215956Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
title |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
spellingShingle |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks Chi, Hao Ran Edge computing Multicriteria decision making (MCDM) Resource allocation Service migration |
title_short |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
title_full |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
title_fullStr |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
title_full_unstemmed |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
title_sort |
Multi-Criteria Dynamic Service Migration for Ultra-Large-Scale Edge Computing Networks |
author |
Chi, Hao Ran |
author_facet |
Chi, Hao Ran Silva, Rui Santos, David Quevedo, José Corujo, Daniel Abboud, Osama Radwan, Ayman Hecker, Artur Aguiar, Rui L. |
author_role |
author |
author2 |
Silva, Rui Santos, David Quevedo, José Corujo, Daniel Abboud, Osama Radwan, Ayman Hecker, Artur Aguiar, Rui L. |
author2_role |
author author author author author author author author |
dc.contributor.author.fl_str_mv |
Chi, Hao Ran Silva, Rui Santos, David Quevedo, José Corujo, Daniel Abboud, Osama Radwan, Ayman Hecker, Artur Aguiar, Rui L. |
dc.subject.por.fl_str_mv |
Edge computing Multicriteria decision making (MCDM) Resource allocation Service migration |
topic |
Edge computing Multicriteria decision making (MCDM) Resource allocation Service migration |
description |
Multiaccess edge computing (MEC) service migration is a technology whose key objective is to support ultralow-latency access to services. However, the complex ultralarge-scale edge service migration problem requires extensive research efforts, regarding the foreseen ultradensified edge nodes in 5G and beyond. In this article, we propose a novel dynamic service migration optimization architecture for ultralarge-scale MEC networks. We develop a new multicriteria decision-making algorithm: Technique for order of preference by similarity to ideal solution with attribute-based Niche count, named TOPANSIS, which showcases its strength to provide an optimal solution for service migration in large-scale deployments towards optimal data rate, latency, and load balancing. We further decentralize the operation of TOPANSIS to release the traffic burden from central datacenters by leveraging local decision making by edge nodes, while relying on central cloud coordination to account for the overall network information. Simulation results showcase that the proposed architecture outperforms the selected benchmarks with an average improvement of 39.41% for latency, 2.92% for data rate, as well as 10.53% and 6.26% for RAM and CPU load balancing, respectively. Moreover, the feasibility of the proposed solution is validated by means of a proof-of-concept implementation and experimental assessments. |
publishDate |
2023 |
dc.date.none.fl_str_mv |
2023-11-01T00:00:00Z 2023-11-01 2026-01-01T00:00:00Z |
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://hdl.handle.net/10773/39947 |
url |
http://hdl.handle.net/10773/39947 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
1551-3203 10.1109/TII.2023.3244321 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/embargoedAccess |
eu_rights_str_mv |
embargoedAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
IEEE |
publisher.none.fl_str_mv |
IEEE |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
collection |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
repository.name.fl_str_mv |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
repository.mail.fl_str_mv |
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1799137750212935680 |