Observatorio de I+D+i UPM

Descripción
Data-related properties of the activities involved in a service composition can be used to facilitate several design-time and run-time adaptation tasks, such as service evolution, distributed enactment, and instance-level adaptation. A number of these properties can be expressed using a notion of sharing. We present an approach for automated inference of data properties based on sharing analysis, which is able to handle service compositions with complex control structures, involving loops and sub-workflows. The properties inferred can include data dependencies, information content, domain-defined attributes, privacy or confidentiality levels, among others. The analysis produces characterizations of the data and the activities in the composition in terms of minimal and maximal sharing, which can then be used to verify compliance of potential adaptation actions, or as supporting information in their generation. This sharing analysis approach can be used both at design time and at run time. In the latter case, the results of analysis can be refined using the composition traces (execution logs) at the point of execution, in order to support run-time adaptation.
Internacional	Si
JCR del ISI	Si
Título de la revista	Computing
ISSN	0010-485X
Factor de impacto JCR	0,701
Información de impacto
Volumen
DOI	10.1007/s00607-012-0230-z
Número de revista
Desde la página	1
Hasta la página	40
Mes	NOVIEMBRE
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• Autor: Dragan Ivanovic . (UPM)
• Autor: Manuel Carro Liñares (UPM)
• Autor: Manuel de Hermenegildo Salinas (UPM)

• Creador: Grupo de Investigación: Computación lógica, Lenguajes, Implementación y Paralelismo (CLIP)
• Departamento: Inteligencia Artificial