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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

Språk

Engelsk

Forfatter(e)

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

Institusjon(er)

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

År

2012

Forlag

Association for Computing Machinery (ACM)

Bok

Proceedings of the 27th Annual ACM Symposium on Applied Computing

ISBN

9781450308571

Side(r)

486 - 491

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