3rd International Conference on Context-Aware Systems and Applications

Research Article

Supporting Runtime Adaptation of Context-Aware Services

  • @INPROCEEDINGS{10.4108/icst.iccasa.2014.257300,
        author={Boudjemaa Boudaa and Slimane Hammoudi and Abdelkader Bouguessa and Mohammed Amine Chikh},
        title={Supporting Runtime Adaptation of Context-Aware Services},
        proceedings={3rd International Conference on Context-Aware Systems and Applications},
        keywords={context-aware service runtime adaptation mape-k mdd},
  • Boudjemaa Boudaa
    Slimane Hammoudi
    Abdelkader Bouguessa
    Mohammed Amine Chikh
    Year: 2015
    Supporting Runtime Adaptation of Context-Aware Services
    DOI: 10.4108/icst.iccasa.2014.257300
Boudjemaa Boudaa1,*, Slimane Hammoudi2, Abdelkader Bouguessa1, Mohammed Amine Chikh3
  • 1: Department of Computer Science, Ibn Khaldoun University, Tiaret, Algeria
  • 2: MODESTE, ESEO, Angers, France
  • 3: Department of Computer Science, Abou Bekr Belkaid University, Tlemcen, Algeria
*Contact email: boudaa.boudjemaa@gmail.com


The intense use of mobile computing cutting-edge devices that characterizes our professional and social lives raises the need to personalise and adapt services according to the dynamic context frequently changes during the execution of these services. In the last decade, the field of context-aware services had led to emerge several works. However, most of the proposed approaches have not provided clear adaptation strategies in case of unforeseen contexts. Dealing with this last at runtime is also another crucial need that has been ignored in their proposals. This paper aims to propose a generic dynamic adaptation process as a phase in the model-driven development life-cycle for context-aware services using the control loop MAPE-K to meet the runtime adaptation. The proposed process is validated by implementing an illustrative example on FraSCAti platform. The principal advantage of this process is to sustain the self-reconfiguration of such services at model and code levels by enabling successive dynamic adaptations depending on volatile context.