LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization

[EN] This paper addresses the issue of quality of service routing optimization within the Internet of Things networks. We particularly focus on the energy-aware and the lightweight aspects. By recognizing the relationship between lightweight and energy-aware routing, we set out to study their combin...

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Detalles Bibliográficos
Autores: Mokrani, Sabrina, Belkadi, Malika, Sadoun, Tassadit, Aoudjit, Rachida, Lloret, Jaime|||0000-0002-0862-0533
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universitat Politècnica de València (UPV)
Repositorio:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
Idioma:inglés
OAI Identifier:oai:riunet.upv.es:10251/220205
Acceso en línea:https://riunet.upv.es/handle/10251/220205
Access Level:acceso abierto
Palabra clave:Quality of service
Lightweight
Energy-aware
Routing
Internet of things
Routing protocol for low power and lossy networks
Particle swarm optimization
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spelling LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimizationMokrani, SabrinaBelkadi, MalikaSadoun, TassaditAoudjit, RachidaLloret, Jaime|||0000-0002-0862-0533Quality of serviceLightweightEnergy-awareRoutingInternet of thingsRouting protocol for low power and lossy networksParticle swarm optimization[EN] This paper addresses the issue of quality of service routing optimization within the Internet of Things networks. We particularly focus on the energy-aware and the lightweight aspects. By recognizing the relationship between lightweight and energy-aware routing, we set out to study their combined benefits. This study aims to enhance the Routing Protocol for Low Power and Lossy Networks by integrating energy-awareness and lightweight characteristics based on the Particle Swarm Optimization algorithm. Our approach addresses energy consumption, routing overhead and decision complexity in route establishment. The principal contributions include the introduction of an objective function that considers Expected Life Time, Delay and a new proposed metric Energy Aware-Expected Transmission Count. The improvement of the Long Short Term Memory predicting inertia weight based PSO with Online Gradient Descent that is used to optimize both the parent selection process and Trickle Timer mechanism. The controlled parent switching process to solve unnecessary and frequent changes. Our approach is validated through simulations in Contiki COOJA, with thorough comparisons with some existing protocols based on packet delivery ratio, average energy consumption, convergence time, control overhead, average end-to-end delay and average parent switching as performance metrics. The results reveal that our approach performs better. Depending on the protocol used for comparison, our approach reduced parent switching by 42.59-61.73%, convergence time by 20.31-66.06%, control overhead by 14.4-23.64%, energy consumption by 29.86-49.6%, end-to-end delay by 7.66-40.81% and increased packet delivery ratio by 2-42.92%.This work has been funded by the "Ministerio de Economia y Competitividad" through the Project TED2021-131040B-C31.Springer-VerlagDepartamento de ComunicacionesEscuela Politécnica Superior de GandiaMinisterio de Economía y CompetitividadUniversitat Politècnica de ValènciaRepositorio Institucional de la Universitat Politècnica de València Riunet20252025-03-01journal articlehttp://purl.org/coar/resource_type/c_6501VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://riunet.upv.es/handle/10251/220205reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valénciainstname:Universitat Politècnica de València (UPV)InglésengMinisterio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TED2021-131040B-C31open accesshttp://purl.org/coar/access_right/c_abf2Reconocimiento (by)http://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:riunet.upv.es:10251/2202052026-06-13T07:49:27Z
dc.title.none.fl_str_mv LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
title LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
spellingShingle LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
Mokrani, Sabrina
Quality of service
Lightweight
Energy-aware
Routing
Internet of things
Routing protocol for low power and lossy networks
Particle swarm optimization
title_short LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
title_full LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
title_fullStr LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
title_full_unstemmed LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
title_sort LEA-RPL: lightweight energy-aware RPL protocol for internet of things based on particle swarm optimization
dc.creator.none.fl_str_mv Mokrani, Sabrina
Belkadi, Malika
Sadoun, Tassadit
Aoudjit, Rachida
Lloret, Jaime|||0000-0002-0862-0533
author Mokrani, Sabrina
author_facet Mokrani, Sabrina
Belkadi, Malika
Sadoun, Tassadit
Aoudjit, Rachida
Lloret, Jaime|||0000-0002-0862-0533
author_role author
author2 Belkadi, Malika
Sadoun, Tassadit
Aoudjit, Rachida
Lloret, Jaime|||0000-0002-0862-0533
author2_role author
author
author
author
dc.contributor.none.fl_str_mv Departamento de Comunicaciones
Escuela Politécnica Superior de Gandia
Ministerio de Economía y Competitividad
Universitat Politècnica de València
Repositorio Institucional de la Universitat Politècnica de València Riunet
dc.subject.none.fl_str_mv Quality of service
Lightweight
Energy-aware
Routing
Internet of things
Routing protocol for low power and lossy networks
Particle swarm optimization
topic Quality of service
Lightweight
Energy-aware
Routing
Internet of things
Routing protocol for low power and lossy networks
Particle swarm optimization
description [EN] This paper addresses the issue of quality of service routing optimization within the Internet of Things networks. We particularly focus on the energy-aware and the lightweight aspects. By recognizing the relationship between lightweight and energy-aware routing, we set out to study their combined benefits. This study aims to enhance the Routing Protocol for Low Power and Lossy Networks by integrating energy-awareness and lightweight characteristics based on the Particle Swarm Optimization algorithm. Our approach addresses energy consumption, routing overhead and decision complexity in route establishment. The principal contributions include the introduction of an objective function that considers Expected Life Time, Delay and a new proposed metric Energy Aware-Expected Transmission Count. The improvement of the Long Short Term Memory predicting inertia weight based PSO with Online Gradient Descent that is used to optimize both the parent selection process and Trickle Timer mechanism. The controlled parent switching process to solve unnecessary and frequent changes. Our approach is validated through simulations in Contiki COOJA, with thorough comparisons with some existing protocols based on packet delivery ratio, average energy consumption, convergence time, control overhead, average end-to-end delay and average parent switching as performance metrics. The results reveal that our approach performs better. Depending on the protocol used for comparison, our approach reduced parent switching by 42.59-61.73%, convergence time by 20.31-66.06%, control overhead by 14.4-23.64%, energy consumption by 29.86-49.6%, end-to-end delay by 7.66-40.81% and increased packet delivery ratio by 2-42.92%.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-03-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
VoR
http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://riunet.upv.es/handle/10251/220205
url https://riunet.upv.es/handle/10251/220205
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.relation.none.fl_str_mv Ministerio de Economía y Competitividad http://dx.doi.org/10.13039/501100003329 TED2021-131040B-C31
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2
Reconocimiento (by)
http://creativecommons.org/licenses/by/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Springer-Verlag
publisher.none.fl_str_mv Springer-Verlag
dc.source.none.fl_str_mv reponame:RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
instname:Universitat Politècnica de València (UPV)
instname_str Universitat Politècnica de València (UPV)
reponame_str RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
collection RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15.811543

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