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Conference Papers Year : 2013

Improving Context-Awareness in Self-Adaptation Using the DYNAMICO Reference Model


Self-adaptation mechanisms modify target systems dynamically to address adaptation goals, which may evolve continuously due to changes in system requirements. These changes affect values and thresholds of observed context variables and monitoring logic, or imply the addition and/or deletion of context variables, thus compromising self-adaptivity effectiveness under static monitoring infrastructures. Nevertheless, self-adaptation approaches often focus on adapting target systems only rather than monitoring infrastructures. Previously, we proposed DYNAMICO, a reference model for self-adaptive systems where adaptation goals and monitoring requirements change dynamically. This paper presents an implementation of DYNAMICO comprising our SMARTERCONTEXT monitoring infrastructure and QOS-CARE adaptation framework in a self-adaptation solution that maintains its context-awareness relevance. To evaluate our reference model we use self-adaptive system properties and the exemplar to compare the Rainbow system with our DYNAMICO implementation. The results of the evaluation demonstrate the applicability, feasibility, and effectiveness of DYNAMICO, especially for self-adaptive systems with context-awareness requirements.
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hal-00796275 , version 1 (25-06-2013)


  • HAL Id : hal-00796275 , version 1


Gabriel Tamura, Norha Villegas, Haussi Muller, Laurence Duchien, Lionel Seinturier. Improving Context-Awareness in Self-Adaptation Using the DYNAMICO Reference Model. 8th International Symposium on Software Engineering for Adaptive and Self-Managing Systems, May 2013, San Francisco, United States. pp.153-162. ⟨hal-00796275⟩
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