Adina Sirbu, Annapaola Marconi, Marco Pistore, Hanna Eberle, Frank Leymann and Tobias Unger
Proceedings of the 9th IEEE International Conference on Web Services (ICWS), 2011
Used by the ALLOW Ensembles project
A critical aspect for pervasive computing is the possibility to discover and use process knowledge at run time depending on the specific context. This can be achieved by using an underlying service-based application and exploiting its features in terms of dynamic service discovery, selection, and composition. Pervasive process fragments represent a service-based tool that allows to model incomplete and contextual knowledge. This paper provides a solution to automatically compose such fragments into complete processes, according to a specific context and specific goals. The solution is computed by encoding process knowledge, domain knowledge and goals into an AI planning problem. The approach is evaluated on different scenarios stress testing the main characteristics of pervasive process fragments.