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

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

Kategori
Vitenskapelig Kapittel/Artikkel/Konferanseartikkel
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.
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 / Software and Service Innovation
År
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