Mostrar el registro sencillo

dc.contributor.authorVillar Bonet, Eugenio, 1957- 
dc.contributor.authorMerino Calleja, Javier 
dc.contributor.authorPosadas Cobo, Héctor 
dc.contributor.authorHenia, Rafik
dc.contributor.authorRioux, Laurent
dc.contributor.otherUniversidad de Cantabriaes_ES
dc.date.accessioned2020-09-30T14:14:28Z
dc.date.available2020-09-30T14:14:28Z
dc.date.issued2020-10
dc.identifier.issn0308-5953
dc.identifier.issn0141-9331
dc.identifier.otherTEC2017-86722-C4-3-Res_ES
dc.identifier.urihttp://hdl.handle.net/10902/19247
dc.description.abstractModel-Driven Design (MDD) has proven to be a powerful technology to address the development of increasingly complex embedded systems. Beyond complexity itself, challenges come from the need to deal with parallelism and heterogeneity. System design must target different execution platforms with different OSs and HW resources, even bare-metal, support local and distributed systems, and integrate on top of these heterogeneous platforms multiple functional component coming from different sources (developed from scratch, legacy code and third-party code), with different behaviors operating under different models of computation and communication. Additionally, system optimization to improve performance, power consumption, cost, etc. requires analyzing huge lists of possible design solutions. Addressing these challenges require flexible design technologies able to support from a single-source model its architectural mapping to different computing resources, of different kind and in different platforms. Traditional MDD methods and tools typically rely on fixed elements, which makes difficult their integration under this variability. For example, it is unlikely to integrate in the same system legacy code with a third-party component. Usually some re-coding is required to enable such interconnection. This paper proposes a UML/MARTE system modeling methodology able to address the challenges mentioned above by improving flexibility and scalability. This approach is illustrated and demonstrated on a flight management system. The model is flexible enough to be adapted to different architectural solutions with a minimal effort by changing its underlying Model of Computation and Communication (MoCC). Being completely platform independent, from the same model it is possible to explore various solutions on different execution platforms.es_ES
dc.description.sponsorshipThis work has been partially funded by the EU and the Spanish MICINN through the ECSEL MegaMart and Comp4Drones projects and the TEC2017-86722-C4-3-R PLATINO project.es_ES
dc.format.extent18 p.es_ES
dc.language.isoenges_ES
dc.publisherElsevieres_ES
dc.rightsAttribution 4.0 Internationales_ES
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/*
dc.sourceMicroprocessors and Microsystems, 2020, 78, 103244es_ES
dc.titleMega-modeling of complex, distributed, heterogeneous CPS systemses_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.relation.publisherVersionhttps://doi.org/10.1016/j.micpro.2020.103244es_ES
dc.rights.accessRightsopenAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/EC/H2020/826610/eu/Framework of key enabling technologies for safe and autonomous drones’ applications/COMP4DRONES/es_ES
dc.identifier.DOI10.1016/j.micpro.2020.103244
dc.type.versionpublishedVersiones_ES


Ficheros en el ítem

Thumbnail

Este ítem aparece en la(s) siguiente(s) colección(ones)

Mostrar el registro sencillo

Attribution 4.0 InternationalExcepto si se señala otra cosa, la licencia del ítem se describe como Attribution 4.0 International