An architecture for rapid, on-demand service composition

Legacy application designmodels, which are still widely used for developing context-aware applications, incur important limitations. Firstly, embedding contextual dependencies in the form of if-then rules specifying how applications should react to context changes is impractical to accommodate the large variety of possibly even unanticipated context types and their values. Additionally, application development is complicated and challenging, as programmers have to manually determine and encode the associations of all possible combinations of context parameters with application behaviour. In this paper we propose a framework for building context aware applications on-demand, as dynamically composed sequences of calls to services. We present the design and implementation of our system, which employs goal-oriented inferencing for assembling composite services, dynamically monitors their execution, and adapts applications to deal with contex-tual changes. We describe the failure recovery mechanisms we have implemented, allowing the deployment of the system in a non-perfect environment, and avoiding the delays inherent in re-discovering a suitable service instance. By means of experimental evaluation in a realistic infotainment application, we demonstrate the potential of the proposed solution an effective, efficient, and scalable approach.