The Internet of Things (IoT) enables producers of context data like sensors to interact with remote consumers of context data like smart pervasive applications in an entirely decoupled way. However, two important issues are faced by context data distribution, namely providing context information with a sufficient level of quality-i.e. quality of context, QoC-while preserving the privacy of context owners. This article presents the solutions provided by the INCOME middleware framework for addressing these two potentially contradictory issues while hiding the complexity of context data distribution in heterogeneous and large-scale environments. Context producers and consumers not only express their needs in context contracts but also the guarantees they are ready to fulfil. These contracts are then translated into advertisement and subscription filters to determine how to distribute context data. Our experiments on a first open source prototype show that QoC-based filtering and privacy protection using attributed-based access control can be performed at a reasonable cost.
International audienceMobile ad-hoc networks, MANETs, are self-organized and very dynamic systems where processes have no global knowledge of the system. In this paper, we propose a model that characterizes the dynamics of MANETs in the sense that it considers that paths between nodes are dynamically built and the system can have infinitely many processes but the network may present finite stable partitions. We also propose an algorithm that implements an eventually perfect partition participant detector PD which eventually detects the participant nodes of stable partitions
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