dc.creator | Ayala, Inmaculada | es |
dc.creator | Amor, Mercedes | es |
dc.creator | Horcas Aguilera, José Miguel | es |
dc.creator | Fuentes, Lidia | es |
dc.date.accessioned | 2021-06-02T09:42:31Z | |
dc.date.available | 2021-06-02T09:42:31Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Ayala, I., Amor, M., Horcas Aguilera, J.M. y Fuentes, L. (2019). A goal-driven software product line approach for evolving multi-agent systems in the Internet of Things. Knowledge-Based Systems, 184 (November 2019) | |
dc.identifier.issn | 0950-7051 | es |
dc.identifier.uri | https://hdl.handle.net/11441/111292 | |
dc.description.abstract | Multi-agent systems have proved to be a suitable technology for developing self-adaptive Internet of
Things (IoT) systems, able to make the most appropriate decisions to address unexpected situations.
This leads to new opportunities to use multi-agent technologies to develop all kinds of cyber–
physical systems, which usually encompass a high diversity of devices (e.g., new home appliances).
The heterogeneity of devices and the high diversity of the available technology, demand the explicit
modeling of all kinds of variability for ultra-large systems. However, multi-agent systems lack
mechanisms to effectively deal with the different degrees of variability present in these kinds of
systems. Software Product Line (SPL) technologies, including variability models, have been successfully
applied to different domains to explicitly model variability in hardware, system requirements or userintended
goals. In addition, current market trends are unpredictable, imposing novel technologies,
new requirements and goals that must be incorporated immediately into the running systems without
damaging them. In this paper, we combine goal-driven and SPL approaches to develop and drive the
evolution of multi-agent systems in the context of cyber–physical systems. We propose an SPL process
and an evolution process that define a set of models (iStar 2.0 for goals and CVL models for variability)
and algorithms to automatically propagate changes to agents running in multiple heterogeneous
devices, each of them with a different configuration. We illustrate the proposal in the context of a
home energy management system. Finally, we have tested the scalability and performance of the
proposal using randomly generated models. The results show that with our approach it is possible
to manage huge iStar models of 10000 elements in seconds. | es |
dc.description.sponsorship | Junta de Andalucía P12-TIC1814 | es |
dc.description.sponsorship | Ministerio de Economía y Competitividad TASOVA MCIU-AEI TIN2017-90644-REDT | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación HADAS TIN2015-64841-R | es |
dc.description.sponsorship | Ministerio de Ciencia e Innovación MEDEA RTI2018- 099213-B-I00 | es |
dc.format | application/pdf | es |
dc.format.extent | 18 | es |
dc.language.iso | eng | es |
dc.publisher | Elsevier | es |
dc.relation.ispartof | Knowledge-Based Systems, 184 (November 2019) | |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | * |
dc.subject | Software product line | es |
dc.subject | Evolution | es |
dc.subject | Internet of Things | es |
dc.subject | MAS-PL | es |
dc.subject | Goal models | es |
dc.subject | GORE | es |
dc.title | A goal-driven software product line approach for evolving multi-agent systems in the Internet of Things | es |
dc.type | info:eu-repo/semantics/article | es |
dcterms.identifier | https://ror.org/03yxnpp24 | |
dc.type.version | info:eu-repo/semantics/submittedVersion | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.contributor.affiliation | Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos | es |
dc.relation.projectID | P12-TIC1814 | es |
dc.relation.projectID | TASOVA MCIU-AEI TIN2017-90644-REDT | es |
dc.relation.projectID | HADAS TIN2015-64841-R | es |
dc.relation.projectID | MEDEA RTI2018- 099213-B-I00 | es |
dc.relation.publisherversion | https://www.sciencedirect.com/science/article/pii/S0950705119303521 | es |
dc.identifier.doi | 10.1016/j.knosys.2019.104883 | es |
dc.journaltitle | Knowledge-Based Systems | es |
dc.publication.volumen | 184 | es |
dc.publication.issue | November 2019 | es |
dc.contributor.funder | Junta de Andalucía | es |
dc.contributor.funder | Ministerio de Economía y Competitividad (MINECO). España | es |
dc.contributor.funder | Ministerio de Ciencia e Innovación (MICIN). España | es |