Towards Lightweight Dynamic Adaptation A Framework and its Evaluation

Leonardo Manuel Rocha 1 Sabine Moisan 1 Jean-Paul Rigault 1, 2 Sen Sagar 1
1 PULSAR - Perception Understanding Learning Systems for Activity Recognition
CRISAM - Inria Sophia Antipolis - Méditerranée
2 Laboratoire d'Informatique, Signaux, et Systèmes de Sophia-Antipolis (I3S) / Equipe MODALIS
Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Abstract. Many modern systems must run in continually changing contexts. For example, a computer vision system to detect vandalism in train stations must function during the day and at night. The software components for image acquisition and people detection used during daytime may not be the same as those used at night. The system must adapt by replacing running components such as image acquisition from color to infra-red. This adaptation involves context detection, decision on change in components, followed by seamless execution of a new configuration of components. All this must occur at runtime while minimizing the impact of dynamic change on continuity and loss in performance. We present Girgit, a lightweight Python-based framework for building dynamic adaptive software systems. We evaluate it by building a dynamically adaptive vision system followed by performing rigorous experiments to determine its continuity and performance
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Conference papers
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https://hal.inria.fr/inria-00616644
Contributor : Leonardo Manuel Rocha <>
Submitted on : Tuesday, August 23, 2011 - 3:53:46 PM
Last modification on : Monday, November 5, 2018 - 3:52:09 PM

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  • HAL Id : inria-00616644, version 1

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Leonardo Manuel Rocha, Sabine Moisan, Jean-Paul Rigault, Sen Sagar. Towards Lightweight Dynamic Adaptation A Framework and its Evaluation. 12th Argentine Symposium on Software Engineering (ASSE 2011), JAII0 2011, Aug 2011, Córdoba, Argentina. ⟨inria-00616644⟩

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