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Scalable Processing of Context Information with COSMOS

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, for example, 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, data interpretation, and situation identification. We propose the COSMOS framework for processing context information in a scalable manner. This framework is based on the concepts of \emph{context node} and \emph{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 \emph{caching/off-loading} adaptation situation.
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Contributor : Lionel Seinturier <>
Submitted on : Friday, June 15, 2007 - 11:45:11 AM
Last modification on : Tuesday, October 20, 2020 - 9:53:46 AM
Long-term archiving on: : Thursday, April 8, 2010 - 8:21:49 PM


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  • HAL Id : inria-00155045, version 1


Denis Conan, Romain Rouvoy, Lionel Seinturier. Scalable Processing of Context Information with COSMOS. 7th IFIP International Conference on Distributed Applications and Interoperable Systems, 2007, Paphos, Cyprus. pp.210-224. ⟨inria-00155045⟩



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