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The DReAM framework: a logic-inspired approach to reconfigurable system modeling

Maggi, Alessandro (2020) The DReAM framework: a logic-inspired approach to reconfigurable system modeling. Advisor: De Nicola, Prof. Rocco. Coadvisor: Sifakis, Prof. Joseph . pp. 172. [IMT PhD Thesis]

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Modern systems evolve in unpredictable environments and have to continuously adapt their behavior to changing conditions. The DReAM (Dynamic Reconfigurable Architecture Modeling) framework has been designed to address these requirements by offering the tools for modeling reconfigurable dynamic systems effectively. At its core, the framework allows component-based architecture design leveraging a rule-based language, inspired from Interaction Logic. The expressiveness of the language allows us to define the behavior of both components and components aggregates encompassing all aspects of dynamicity, including parametric multi-modal coordination of components and reconfiguration of their structure and population. DReAM allows the description of both endogenous/modular and exogenous/centralized coordination styles and sound transformations from one style to the other, while adopting a familiar and intuitive syntax. To better model dynamic mobile systems, the framework is further extended with two structuring concepts: motifs - independent dynamic architectures coordinating components assigned to them - and maps - graphlike data structures modeling the topology of the environment and parametrizing coordination between components. The jDReAM Java project has been developed to provide an execution engine with an associated library of classes and methods that support system specifications conforming to the DReAM syntax. It allows to develop runnable systems combining the expressiveness of the rule-based notation with the flexibility of this widespread programming language.

Item Type: IMT PhD Thesis
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
PhD Course: Computer science
Identification Number: 10.6092/imtlucca/e-theses/310
NBN Number: urn:nbn:it:imtlucca-27025
Date Deposited: 07 Jul 2020 07:02
URI: http://e-theses.imtlucca.it/id/eprint/310

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