Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU

Autores:: Campo-Muñoz, Wilmar-Yesid
Amaya-Suárez, Jhon-Alexander
Caviedes-Valencia, Juan-Camilo

Tipo de recurso:: Article of journal

Fecha de publicación:: 2024

Institución:: Universidad Pedagógica y Tecnológica de Colombia

Repositorio:: RiUPTC: Repositorio Institucional UPTC

Idioma:

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dc.title.es-ES.fl_str_mv	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
title	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
spellingShingle	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU AMF Autoescalamiento CPU LSTM Políticas de escalamiento Scaling policies Self-scaling
title_short	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
title_full	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
title_fullStr	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
title_full_unstemmed	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
title_sort	Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU
dc.creator.fl_str_mv	Campo-Muñoz, Wilmar-Yesid Amaya-Suárez, Jhon-Alexander Caviedes-Valencia, Juan-Camilo
dc.contributor.author.eng.fl_str_mv	Campo-Muñoz, Wilmar-Yesid Amaya-Suárez, Jhon-Alexander Caviedes-Valencia, Juan-Camilo
dc.subject.none.fl_str_mv	AMF Autoescalamiento CPU LSTM Políticas de escalamiento Scaling policies Self-scaling
topic	AMF Autoescalamiento CPU LSTM Políticas de escalamiento Scaling policies Self-scaling
publishDate	2024
dc.date.accessioned.none.fl_str_mv	2024-08-29 21:27:51 2026-04-16T17:47:37Z
dc.date.available.none.fl_str_mv	2024-08-29 21:27:51
dc.date.issued.none.fl_str_mv	2024-08-29
dc.type.spa.fl_str_mv	Artículo de revista
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dc.identifier.doi.none.fl_str_mv	10.19053/uptc.01211129.v33.n69.2024.18057
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dc.relation.references.none.fl_str_mv	Ericsson, Explore the Ericsson Mobility Report, 2024. https://www.ericsson.com/en/reports-andpapers/mobility-report/reports/june-2024 I. Alam et al., “A Survey of Network Virtualization Techniques for Internet of Things Using SDN and NFV,” ACM Computing Surveys, vol. 53, no. 2, e337944, 2020. https://doi.org/10.1145/3379444 J. L. Chavez-Picon, W. Y. Campo-Muñoz, G. E. Chanchí-Golondrino. “Arquitectura para implementación de servicios de video sobre redes móviles mediante redes definidas por software y segmentación de red,” Revista Colombiana de Tecnologías de Avanzada (RCTA), vol. 2, no. 42, e2651. https://doi.org/10.24054/rcta.v2i42.2651 A. Chouman, D. M. Manias, A. Shami, “A Reliable AMF Scaling and Load Balancing Framework for 5G Core Networks,” in International Wireless Communications and Mobile Computing (IWCMC), Marrakesh, Morocco, 2023, pp. 252-257. https://doi.org/10.1109/IWCMC58020.2023.10182447 H. Atarashi, M. Iwamura, S. Nagata, T. Nakamura, A. Toskala, “5G Targets and Standardization,” in 5G Technoly 3GPP Evolution to 5G-Advanced, pp. 13-26, 2024. A. Toskala, M. Poikselkä, “5G Architecture,” in 5G Technoly 3GPP Evolution to 5G-Advanced, pp. 67-86, 2024. S. Christakis, N. Makris, T. Korakis, S. Fdida, “On the Automated Scaling of User Plane Function for 5G: An Experimental Evaluation,” in Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Belgium, 2024, pp. 979-984. https://doi.org/10.1109/EuCNC/6GSummit60053.2024.10597110 C. Rotter, T. Van Do, “A Queueing Model for Threshold-Based Scaling of UPF Instances in 5G Core,” IEEE Access, vol. 9, pp. 81443-81453, 2021. https://doi.org/10.1109/ACCESS.2021.3085955 T. Lorido-Botran, J. Miguel-Alonso, J. A. Lozano, “A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments,” Journal of Grid Computing., vol. 12, no. 4, pp. 559-592, 2014. https://doi.org/10.1007/s10723-014-9314-7 J. C. Valencia, “Modelo predictivo para la asignación elástica de recursos sobre entornos NFV/SDN basados en OpenStack,” Grade Thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2021. https://repositorio.unal.edu.co/handle/unal/79636 I. Alawe, A. Ksentini, Y. Hadjadj-Aoul, P. Bertin, “Improving Traffic Forecasting for 5G Core Network Scalability: A Machine Learning Approach,” IEEE Network, vol. 32, no. 6, pp. 42-49, 2018. https://doi.org/10.1109/MNET.2018.1800104 I. Alawe, A. Ksentini, Y. Hadjadj-Aoul, P. Bertin, A. Kerbellec, “On evaluating different trends for virtualized and SDN-ready mobile network,” in IEEE 6th International Conference in Cloud Networking, 2017. https://doi.org/10.1109/CloudNet.2017.8071534 M. A. Alam, S. Khatibi, “CPU resource usage analysis for downlink PDCP processing in CRAN,” in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2020. https://doi.org/10.1109/PIMRC48278.2020.9217294 H. D. Trinh, L. Giupponi, P. Dini, “Mobile Traffic Prediction from Raw Data Using LSTM Networks,” IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2018, pp. 1827-1832. https://doi.org/10.1109/PIMRC.2018.8581000 L. Nashold, R. Krishnan, Using LSTM and SARIMA Models to Forecast Cluster CPU Usage, 2020. https://api.semanticscholar.org/CorpusID:219711129 H. Ge, Y. Huo, Z. Wang, P. Xie, T. Wei, “VNF Instance Dynamic Scaling Strategy Based on LSTM,” Advances in Intelligent Systems and Computing, vol. 1274, pp. 335-343, 2021. https://doi.org/10.1007/978-981-15-8462-6_39
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dc.relation.citationissue.eng.fl_str_mv	69
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dc.relation.citationvolume.eng.fl_str_mv	33
dc.relation.ispartofjournal.eng.fl_str_mv	Revista Facultad de Ingeniería
dc.relation.bitstream.none.fl_str_mv	https://revistas.uptc.edu.co/index.php/ingenieria/article/download/18057/14934 https://revistas.uptc.edu.co/index.php/ingenieria/article/download/18057/14707
dc.relation.citationedition.eng.fl_str_mv	Núm. 69 , Año 2024 : July-September 2024: Open Science at the Service of Engineering
dc.rights.none.fl_str_mv	Wilmar-Yesid Campo-Muñoz, Jhon-Alexander Amaya-Suárez, Juan-Camilo Caviedes-Valencia - 2024
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rights_invalid_str_mv	Wilmar-Yesid Campo-Muñoz, Jhon-Alexander Amaya-Suárez, Juan-Camilo Caviedes-Valencia - 2024 https://creativecommons.org/licenses/by/4.0 This work is licensed under a Creative Commons Attribution 4.0 International License. http://purl.org/coar/access_right/c_abf2
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spelling	Campo-Muñoz, Wilmar-YesidAmaya-Suárez, Jhon-AlexanderCaviedes-Valencia, Juan-Camilo2024-08-29 21:27:512026-04-16T17:47:37Z2024-08-29 21:27:512024-08-290121-1129https://repositorio.uptc.edu.co/handle/001/2158610.19053/uptc.01211129.v33.n69.2024.180572357-5328https://doi.org/10.19053/uptc.01211129.v33.n69.2024.18057text/xmlapplication/pdfUniversidad Pedagógica y Tecnológica de ColombiaWilmar-Yesid Campo-Muñoz, Jhon-Alexander Amaya-Suárez, Juan-Camilo Caviedes-Valencia - 2024https://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessThis work is licensed under a Creative Commons Attribution 4.0 International License.http://purl.org/coar/access_right/c_abf2https://revistas.uptc.edu.co/index.php/ingenieria/article/view/18057AMFAutoescalamientoCPULSTMPolíticas de escalamientoScaling policiesSelf-scalingAnálisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPUArtículo de revistahttp://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1info:eu-repo/semantics/articleJournal articleinfo:eu-repo/semantics/publishedVersionTexthttp://purl.org/coar/version/c_970fb48d4fbd8a85Ericsson, Explore the Ericsson Mobility Report, 2024. https://www.ericsson.com/en/reports-andpapers/mobility-report/reports/june-2024I. Alam et al., “A Survey of Network Virtualization Techniques for Internet of Things Using SDN and NFV,” ACM Computing Surveys, vol. 53, no. 2, e337944, 2020. https://doi.org/10.1145/3379444J. L. Chavez-Picon, W. Y. Campo-Muñoz, G. E. Chanchí-Golondrino. “Arquitectura para implementación de servicios de video sobre redes móviles mediante redes definidas por software y segmentación de red,” Revista Colombiana de Tecnologías de Avanzada (RCTA), vol. 2, no. 42, e2651. https://doi.org/10.24054/rcta.v2i42.2651A. Chouman, D. M. Manias, A. Shami, “A Reliable AMF Scaling and Load Balancing Framework for 5G Core Networks,” in International Wireless Communications and Mobile Computing (IWCMC), Marrakesh, Morocco, 2023, pp. 252-257. https://doi.org/10.1109/IWCMC58020.2023.10182447H. Atarashi, M. Iwamura, S. Nagata, T. Nakamura, A. Toskala, “5G Targets and Standardization,” in 5G Technoly 3GPP Evolution to 5G-Advanced, pp. 13-26, 2024.A. Toskala, M. Poikselkä, “5G Architecture,” in 5G Technoly 3GPP Evolution to 5G-Advanced, pp. 67-86, 2024.S. Christakis, N. Makris, T. Korakis, S. Fdida, “On the Automated Scaling of User Plane Function for 5G: An Experimental Evaluation,” in Joint European Conference on Networks and Communications & 6G Summit (EuCNC/6G Summit), Belgium, 2024, pp. 979-984. https://doi.org/10.1109/EuCNC/6GSummit60053.2024.10597110C. Rotter, T. Van Do, “A Queueing Model for Threshold-Based Scaling of UPF Instances in 5G Core,” IEEE Access, vol. 9, pp. 81443-81453, 2021. https://doi.org/10.1109/ACCESS.2021.3085955T. Lorido-Botran, J. Miguel-Alonso, J. A. Lozano, “A Review of Auto-scaling Techniques for Elastic Applications in Cloud Environments,” Journal of Grid Computing., vol. 12, no. 4, pp. 559-592, 2014. https://doi.org/10.1007/s10723-014-9314-7J. C. Valencia, “Modelo predictivo para la asignación elástica de recursos sobre entornos NFV/SDN basados en OpenStack,” Grade Thesis, Universidad Nacional de Colombia, Bogotá, Colombia, 2021. https://repositorio.unal.edu.co/handle/unal/79636I. Alawe, A. Ksentini, Y. Hadjadj-Aoul, P. Bertin, “Improving Traffic Forecasting for 5G Core Network Scalability: A Machine Learning Approach,” IEEE Network, vol. 32, no. 6, pp. 42-49, 2018. https://doi.org/10.1109/MNET.2018.1800104I. Alawe, A. Ksentini, Y. Hadjadj-Aoul, P. Bertin, A. Kerbellec, “On evaluating different trends for virtualized and SDN-ready mobile network,” in IEEE 6th International Conference in Cloud Networking, 2017. https://doi.org/10.1109/CloudNet.2017.8071534M. A. Alam, S. Khatibi, “CPU resource usage analysis for downlink PDCP processing in CRAN,” in IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2020. https://doi.org/10.1109/PIMRC48278.2020.9217294H. D. Trinh, L. Giupponi, P. Dini, “Mobile Traffic Prediction from Raw Data Using LSTM Networks,” IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, 2018, pp. 1827-1832. https://doi.org/10.1109/PIMRC.2018.8581000L. Nashold, R. Krishnan, Using LSTM and SARIMA Models to Forecast Cluster CPU Usage, 2020. https://api.semanticscholar.org/CorpusID:219711129H. Ge, Y. Huo, Z. Wang, P. Xie, T. Wei, “VNF Instance Dynamic Scaling Strategy Based on LSTM,” Advances in Intelligent Systems and Computing, vol. 1274, pp. 335-343, 2021. https://doi.org/10.1007/978-981-15-8462-6_39e1805769e1805733Revista Facultad de Ingenieríahttps://revistas.uptc.edu.co/index.php/ingenieria/article/download/18057/14934https://revistas.uptc.edu.co/index.php/ingenieria/article/download/18057/14707Núm. 69 , Año 2024 : July-September 2024: Open Science at the Service of EngineeringPublicationOREORE.xmltext/xml2763https://repositorio.uptc.edu.co/bitstreams/5b791288-9007-4f53-a59e-95049034d45c/download5be10c54876484b01fc9de16965e1d16MD51falseAnonymousREAD001/21586oai:repositorio.uptc.edu.co:001/215862026-10-29 14:04:45.002https://creativecommons.org/licenses/by/4.0metadata.onlyhttps://repositorio.uptc.edu.coRepositorio Institucional UPTCbdigital@metabiblioteca.com

Análisis de desempeño de la función de gestión de acceso y movilidad en un Core 5G basado en predicciones del uso de CPU

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