From ambient sensing to IoT-based context computing: an open framework for end to end QoC management

Pierrick Marie (1, 2) , Thierry Desprats (1, 2) , Sophie Chabridon (3, 4, 5) , Michelle Sibilla (1, 2) , Chantal Taconet (3, 4, 5)

1 IRIT-SIERA - Service IntEgration and netwoRk Administration
2 UT3 - Université Toulouse III - Paul Sabatier
3 TSP - INF - Département Informatique
4 SAMOVAR - Services répartis, Architectures, MOdélisation, Validation, Administration des Réseaux
5 CNRS - Centre National de la Recherche Scientifique

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.

Mots clés: Information model; Meta-modeling; Context management; Quality criterion; Quality of Context

Domaines: Calcul parallèle, distribué et partagé [cs.DC]; Génie logiciel [cs.SE]

Pierrick Marie, Thierry Desprats, Sophie Chabridon, Michelle Sibilla, Chantal Taconet. From ambient sensing to IoT-based context computing: an open framework for end to end QoC management. Sensors, 2015, Special Issue: Select Papers from UCAmI & IWAAL 2014, 15 (6), pp.14180-14206. ⟨10.3390/s150614180⟩. ⟨hal-01262395⟩