Quality-aware analysis and optimisation of virtual network functions.

dc.centroE.T.S.I. Informáticaes_ES
dc.contributor.authorMuñoz-Guerra, Daniel Jesús
dc.contributor.authorPinto-Alarcón, Mónica
dc.contributor.authorFuentes-Fernández, Lidia
dc.date.accessioned2025-12-04T10:17:55Z
dc.date.available2025-12-04T10:17:55Z
dc.date.issued2022-09-12
dc.departamentoInstituto de Tecnología e Ingeniería del Software de la Universidad de Málagaes_ES
dc.departamentoLenguajes y Ciencias de la Computaciónes_ES
dc.descriptionThis work is supported by the European Union’s H2020 research and innovation programme under grant agreementDAEMON101017109, by the projects co-financed by FEDER funds LEIA UMA18-FEDERJA- 15, MEDEA RTI2018-099213-B-I00 and Rhea P18-FR-1081 and the PRE2019-087496 grant from the Ministerio de Ciencia e Innovación.es_ES
dc.descriptionhttps://authors.acm.org/author-resources/author-rightses_ES
dc.description.abstractThe softwarisation and virtualisation of network functionality is the last milestone in the networking industry. Software-Defined Networks (SDN) and Network Function Virtualization (NFV) offer the possibility of using software to manage computer and mobile networks and build novel Virtual Network Functions (VNFs) deployed in heterogeneous devices. To reason about the variability of network functions and especially about the quality of a software product defined as a set of VNFs instantiated as part of a service (i.e., Service Function Chaining), a variability model along with a quality model is required. However, this domain imposes certain challenges to quality-aware reasoning of service function chains, such as numerical features or configuration-level Quality Attributes (QAs) (e.g., energy consumption). Incorporating numerical reasoning with quality data into SPL analyses is challenging and tool support is rare. In this work, we present 3 groups of operations: model report, aggregate functions to dynamically convert QAs at the feature-level into the configuration-level, and quality-aware optimisation. Our objective is to test the most complete reasoning tools to exploit the extended variability with quality attributes needed for VNFs.es_ES
dc.identifier.doi10.1145/3546932.3547007
dc.identifier.isbn9781450394437
dc.identifier.urihttps://hdl.handle.net/10630/40992
dc.language.isoenges_ES
dc.publisherAssociation for Computing Engineering (ACM)es_ES
dc.relation.eventdate12 a 16 Septiembre 2022es_ES
dc.relation.eventplaceGraz, Austriaes_ES
dc.relation.eventtitle26th ACM International Systems and Software Product Line Conference, SPLC 2022es_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/101017109/EU/Network intelligence for aDAptive and sElf-learning MObile Networks/DAEMONes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Andalucia/FEDER/UMA18-FEDERJA-15/ES/LEIA/LEIAes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Ministerio de Ciencia e Innovacion/Retos Investigacion/RTI2018-099213-B-I00/ES/Metodologías para el Desarrollo de Aplicaciones IoT de Extremo a Extremo/MEDEAes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Junta de Andalucia/PAIDI 2020/P18-FR-1081/ES/Reingeniería para la Heterogeneidad y Evolución de Aplicaciones/Rheaes_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/Ministerio de Ciencia e Innovacion/FPI/PRE2019-087496/ES/Ayudas para contratos predoctorales para la formación de doctores/PRE2019es_ES
dc.rights.accessRightsopen accesses_ES
dc.subjectIngeniería del softwarees_ES
dc.subject.otherVirtual network functiones_ES
dc.subject.otherQuality attributees_ES
dc.subject.otherVariabilityes_ES
dc.subject.otherNumerical featurees_ES
dc.subject.otherReasoninges_ES
dc.subject.otherOptimizationes_ES
dc.titleQuality-aware analysis and optimisation of virtual network functions.es_ES
dc.typeconference outputes_ES
dspace.entity.typePublication
relation.isAuthorOfPublication839f00c1-d583-4eeb-bb1e-d529b1df6967
relation.isAuthorOfPublication431c7076-c749-483c-8fd6-b9c18bf33a13
relation.isAuthorOfPublication.latestForDiscovery839f00c1-d583-4eeb-bb1e-d529b1df6967

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