International audienceMaking the Internet of Things (IoT) a reality will contribute to extend the context-aware ability of numerous sensitive applications. We can foresee that the context of users will include not only their own spatio-temporal conditions but also those of the things situated in their ambient environment and at the same time, thanks to the IoT, those that are located in other remote spaces. Consequently, next-generation context managers have to interact with the IoT underlying technologies and must, even more than before, address both privacy and quality of context (QoC) requirements. In this article, we show that the notions of privacy and QoC are intimately related and sometimes contradictory and survey the recent works addressing them. Current solutions usually consider only one notion, and very few of them started to bridge privacy and QoC. We identify some of the remaining challenges that next-generation context managers have to deal with to favour users' acceptability by providing both the optimal QoC level and the appropriate privacy protectio

In the last decade, several works proposed their own list of quality of context (QoC) criteria. This article relates a comparative study of these successive propositions. The result is that no consensus has been reached about the semantic and the comprehensiveness of QoC criteria. Facing this situation, the QoCIM meta-model offers a generic, computable and expressive solution to handle and to exploit any QoC criterion within distributed context managers and context-aware applications. For validation purposes, QoCIM is successfully applied to the modelling of a set of simple and composite QoC criteria.

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.

OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.

Quality of Context (QoC) awareness is recognized as a key point for the success of context-aware computing. At the time where the combination of the Internet of Things, Cloud Computing, and Ambient Intelligence paradigms offer together new opportunities for managing richer context data, the next generation of Distributed Context Managers (DCM) is facing new challenges concerning QoC management. This paper presents our model-driven QoCIM framework. QoCIM is the acronym for Quality of Context Information Model. We show how it can help application developers to manage the whole QoC life-cycle by providing genericity, openness and uniformity. Its usages are illustrated, both at design time and at runtime, in the case of an urban pollution context- and QoC-aware scenario.

In the last decade, several works proposed their own list of quality of context (QoC) criteria. This article relates a comparative study of these successive propositions and shows that no consensus has been reached about the semantic and the comprehensiveness of QoC criteria. Facing this situation, the QoCIM meta-model offers a generic, computable and expressive solution to handle and exploit any QoC criterion within distributed context managers and context-aware applications. For validation purposes, the key modelling features of QoCIM are illustrated as well as the tool chain that provides developers with QoCIM based models editor and code generator. With the tool chain, developers are able to define and use their own QoC criteria within context and quality aware applications.

OATAO is an open access repository that collects the work of Toulouse researchers and makes it freely available over the web where possible.

This paper discusses the requirements of situation identification in the Internet of Things and the necessity to consider the quality of the input context data during the inference process for deriving a situation and evaluating its resulting quality. We propose to extend previous works by integrating the QoCIM meta-model within the muSIC framework dedicated to situation identification. Situation identification is derived using an ontological approach and Quality criteria are aggregated using the fuzzy Choquet operator for computing the quality of a situation. This paper shows that QoCIM allows to model quality of context (QoC) as well as quality of situation in a unified approach.