Published October 5, 2009
| Version v1
Conference paper
Modeling Context and Dynamic Adaptations with Feature Models
- Others:
- Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS ; Scalable and Pervasive softwARe and Knowledge Systems (Laboratoire I3S - SPARKS) ; Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Laboratoire d'Informatique, Signaux, et Systèmes de Sophia Antipolis (I3S) ; Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)-Université Nice Sophia Antipolis (1965 - 2019) (UNS) ; COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Centre National de la Recherche Scientifique (CNRS)-Université Côte d'Azur (UCA)
- Stiftelsen for INdustriell og TEknisk Forskning Digital [Trondheim] (SINTEF Digital)
- Perception Understanding Learning Systems for Activity Recognition (PULSAR) ; Inria Sophia Antipolis - Méditerranée (CRISAM) ; Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)
Description
Self-adaptive and dynamic systems adapt their behavior according to the context of execution. The contextual information exhibits multiple variability factors which induce many possible configurations of the software system at runtime. The challenge is to specify the adaptation rules that can link the dynamic variability of the context with the possible variants of the system. Our work investigates the systematic use of feature models for modeling the context and the software variants, together with their inter relations, as a way to configure the adaptive system with respect to a particular context. A case study in the domain of video surveillance systems is used to illustrate the approach.
Abstract
International audience
Additional details
- URL
- https://hal.archives-ouvertes.fr/hal-00419990
- URN
- urn:oai:HAL:hal-00419990v1
- Origin repository
- UNICA