Abstract. Ubiquitous computing environments are characterised by a high number of heterogeneous devices that generate a huge amount of context data. These data are used to adapt applications to changing execution contexts. However, legacy frameworks fail to process context information in a scalable and efficient manner. In this paper, we propose to organise the classical functionalities of a context manager to introduce a 3-steps cycle of data collection, interpretation, and situation identification. We propose the COSMOS framework, which is based on the concepts of context node and context management policies translated into software components in software architecture. This paper presents COSMOS and evaluates its efficiency throughout the example of the composition of context information to implement a caching/off-loading adaptation situation.

Ubiquitous applications are characterised by variations of their execution context. Their correct operation requires some continual adaptations based on the observation of their execution context. The design and the implementation of these observation policies is then the cornerstone of any ubiquitous applications. In this article, we propose COSMOS which is a framework for the principled specification and composition of context observation policies. With COSMOS, these policies are decomposed into fine-grained units called context nodes implemented as software components. These units perform basic context-related operations (e.g., gathering data from a system or network probe, computing threshold or average values) and are assembled with a set of well-identified architectural design patterns. In this article, COSMOS is motivated and illustrated with an example from the domain of mobile e-commerce applications.

Abstract. Context-aware computing has to deal with a huge amount of context data. Taking into account the quality of these data becomes a corner stone of an efficient context management solution. Information on the quality of context helps taking appropriate decisions and allows to identify uncertain context information saving processing time for deriving a pertinent description of the observed phenomenon. This paper presents a work in progress for integrating Quality of Context in COSMOS (COntext entitieS coMpositiOn and Sharing) [4,13], a component-based framework for managing context data in ubiquitous environments, and illustrates it throughout the example of the composition of context information to implement a network connectivity vs energy adaptation situation.

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