We present an approach to reasoning on complex adaptive software architectures able to dynamically design and change features of the model according to changed behavioral properties or context variables and parameters. The approach consists of a metamodel composed by a Knowledge Graph(KG) and case-based reasoning to find a path connecting state, context and action on the KG. The metamodel allows to derive a runtime architectural model of adaptive application from high level goals and operational requirements, and enable runtime composi tion of the layout of a decentralized and distributed complex application. To validate the metamodel we also propose an instantiation in two real scenarios in order to exploit both requirements and architectural model.

Case-based reasoning and knowledge-graph based metamodel for runtime adaptive architectural modeling / Mongiello, Marina; DI NOIA, Tommaso; Nocera, Francesco; DI SCIASCIO, Eugenio. - (2016), pp. 1323-1328. (Intervento presentato al convegno 31st Annual ACM Symposium on Applied Computing, SAC 2016 tenutosi a Pisa, Italy nel April 4 -8, 2016) [10.1145/2851613.2851767].

Case-based reasoning and knowledge-graph based metamodel for runtime adaptive architectural modeling

MONGIELLO, Marina;DI NOIA, Tommaso;NOCERA, FRANCESCO;DI SCIASCIO, Eugenio
2016-01-01

Abstract

We present an approach to reasoning on complex adaptive software architectures able to dynamically design and change features of the model according to changed behavioral properties or context variables and parameters. The approach consists of a metamodel composed by a Knowledge Graph(KG) and case-based reasoning to find a path connecting state, context and action on the KG. The metamodel allows to derive a runtime architectural model of adaptive application from high level goals and operational requirements, and enable runtime composi tion of the layout of a decentralized and distributed complex application. To validate the metamodel we also propose an instantiation in two real scenarios in order to exploit both requirements and architectural model.
2016
31st Annual ACM Symposium on Applied Computing, SAC 2016
978-1-4503-3739-7
Case-based reasoning and knowledge-graph based metamodel for runtime adaptive architectural modeling / Mongiello, Marina; DI NOIA, Tommaso; Nocera, Francesco; DI SCIASCIO, Eugenio. - (2016), pp. 1323-1328. (Intervento presentato al convegno 31st Annual ACM Symposium on Applied Computing, SAC 2016 tenutosi a Pisa, Italy nel April 4 -8, 2016) [10.1145/2851613.2851767].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11589/89475
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