Abstract. To realise an Ambient Intelligence environment, it is paramount that applications can dispose of information about the context in which they operate, preferably in a very general manner. For this purpose various types of information should be assembled to form a representation of the context of the device on which aforementioned applications run. To allow interoperability in an Ambient Intelligence environment, it is necessary that the context terminology is commonly understood by all participating devices. In this paper we propose an adaptable and extensible context ontology for creating context-aware computing infrastructures, ranging from small embedded devices to high-end service platforms. The ontology has been designed to solve several key challenges in Ambient Intelligence, such as application adaptation, automatic code generation and code mobility, and generation of device specific user interfaces.
This paper proposes a way to realize the idea of calm computing by adding a dynamic task model into the pervasive computing environment. This task model contains information about the actions to undertake to help a user realize his daily tasks. The task model's mapping onto a deployment plan guides an internal adaptation mechanism, which helps applications to evolve without causing user distraction. In addition, a foraging technique (relocation) is proposed that allows for expanding an application's computing space automatically whenever possible. This technique involves external adaptation mechanisms. Both adaptation mechanisms are driven by resource information and resource contracts that are negotiated between the middleware and the application components. This allows the middleware to do the adaptations automatically, realizing the idea of calm computing.
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