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. 2015 Jun 16;15(6):14180-206.
doi: 10.3390/s150614180.

From Ambient Sensing to IoT-based Context Computing: An Open Framework for End to End QoC Management

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From Ambient Sensing to IoT-based Context Computing: An Open Framework for End to End QoC Management

Pierrick Marie et al. Sensors (Basel). .

Abstract

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.

Keywords: Quality of Context; context management; information model; meta-modeling; quality criterion.

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Figures

Figure 1
Figure 1
Pollution measurement scenario.
Figure 2
Figure 2
QoCIM meta-model.
Figure 3
Figure 3
The QoCIM-based graphical editor.
Figure 4
Figure 4
The main functionalities of a context manager.
Figure 5
Figure 5
The four points where the QoCIM framework operates.
Figure 6
Figure 6
Example of pollution measurements sequence executed in a bus.
Figure 7
Figure 7
Overview of the routing filters within a distributed context manager.
Figure 8
Figure 8
The routing filters used in the scenario to provide the pollution level of a street.

References

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