Til hovedinnhold
Norsk English

Using Constraint-based Optimization and Variability to Support Continuous Self-Adaptation

Sammendrag

Self-adaptation is one of the upcoming paradigms that accurately tackles nowadays systems complexity. In this context, Dynamic Software Product Lines model the intrinsic variability of a family of systems, and dynamically support their reconfiguration according to updated context. However, when several configurations are available for the same context, making a decision about the right one is a hard challenge: further dimensions such as QoS are needed to enrich the decision making process. In this paper, we propose to combine variability with Constraint-Satisfaction Problem techniques to face this challenge. The approach is illustrated and validated with a context-driven system used to support the control of a home through mobile devices.

Kategori

Vitenskapelig Kapittel/Artikkel/Konferanseartikkel

Språk

Engelsk

Forfatter(e)

  • Carlos Andres Parra
  • Daniel Romero
  • Sébastien Mosser
  • Romain Rouvoy
  • Laurence Duchien
  • Lionel Seinturier

Institusjon(er)

  • Institut National de Recherche en Informatique et en Automatique
  • SINTEF Digital / Sustainable Communication Technologies

År

2012

Forlag

Association for Computing Machinery (ACM)

Bok

Proceedings of the 27th Annual ACM Symposium on Applied Computing

ISBN

978-1-4503-0857-1

Side(r)

486 - 491

Vis denne publikasjonen hos Cristin