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Modeling self-configuration in Architecture-based self-adaptive systems

Abstract : Modern systems are pressured to adapt in response to their constantly changing environment to remain useful. Traditionally, this adaptation has been handled at down times of the system. there is an increased demand to automate this process and achieve it whilst the system is running. Self-adaptive systems were introduced as a realization of continuously adapting systems. Self-adaptive systems are able to modify at runtime their behavior and/or structure in response to their perception of the environment, the system itself, and their requirements. The focus of this work is on realizing self-configuration, a key and essential property of self-adaptive systems. Self-configuration is the capability of reconfiguring automatically and dynamically in response to changes. This may include installing, integrating, removing and composing/decomposing system elements.This thesis introduces the Dr-BIP framework, an extension of the BIP framework for modeling self-configuring systems that relies on a model-based and component & connector approach to prescribe systems. The combination of both of these approaches exploits the benefits of each, making their combination an ideal methodology to realize complex self-configuring systems.A Dr-BIP system model is a runtime model which captures the running system at three different levels of abstraction namely behavior, configuration, and configuration variants. The system's configuration is captured by component and connectors. In a component and connector system, self-configuration can have three different levels of granularity which includes the ability to add or remove connectors, add or remove components, and add or remove subsystems. Dr-BIP supports explicit addition and removal of both components and subsystems, but implicit addition and removal of connectors. The main advantage of relying on an implicit addition and removal of connectors is the ability to guarantee by construction specific configuration topologies.To capture the three levels of abstraction, we introduce motifs as primary structures to prescribe a self-configuring Dr-BIP system. A motif defines a set of components that evolve according to interaction and reconfiguration rules. A system is composed of multiple motifs that possibly share components and evolve together. Interaction rules dictate how components composing the system can interact and reconfiguration rules dictate how the system configuration can evolve over time. Finally, we show that the proposed framework is both minimal and expressive by modeling four different self-configuring systems. Last but not least, we propose a modeling language to codify the framework concepts and provision an interpreter implementation.
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Submitted on : Friday, July 5, 2019 - 4:29:08 PM
Last modification on : Wednesday, March 31, 2021 - 3:14:08 AM


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  • HAL Id : tel-02175324, version 1



Rim El Ballouli. Modeling self-configuration in Architecture-based self-adaptive systems. Artificial Intelligence [cs.AI]. Université Grenoble Alpes, 2019. English. ⟨NNT : 2019GREAM007⟩. ⟨tel-02175324⟩



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