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Self-Adaptable Discovery and Composition of Services Based on the Semantic CompAA Approach
Abstract
With the next generation of distributed systems, applications become nomad, ubiquitous or ambient. It becomes challenging to dynamically maintain or update functionalities, or to preserve non-functional properties, like the extensibility of the system and the quality of service. This paper describes the CompAA component model. The main contribution introduces the variability concept with the specification of adaptation points integrated by a mixed component/agent approach. The result is the production of self-adaptable entities, including self-discovery and self-composition mechanisms. An experiment in the area of training, based on very scalable services (e-Portfolio), validates these contributions and provides an exemplification of CompAA mechanisms.
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