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.
Highlights
Context-aware applications become widely available and are entering our everyday lives
The purpose of the Quality of Context Information Model (QoCIM) meta-model is to offer a solution to define Quality of Context (QoC) criteria that could be: primitive: a criterion that does not depend on any other criteria for its definition, for example, the usability in Table 2; composite: a criterion built upon other criteria, as for the timeliness criterion in Table 2; invariant: a criterion that has a well defined list of possible values, for example, the accuracy criterion illustrated in the pollution scenario
We modeled QoCIM as an Ecore model based on the EMF technology [19] and we developed a graphical editor with the Sirius technology [20]
Summary
Context-aware applications become widely available and are entering our everyday lives These applications consume context information extracted from local ambient data, user profiles, collected from heterogeneous and spatially distributed sensors. New challenges arise in order to guarantee the effectiveness and the efficiency of the new generation of context managers, corresponding to Distributed Context Managers (DCMs). Such DCMs must be deployed at multiple scales over various devices or servers, spread across heterogeneous networks. In addition to the classical key points used for the successful determination of the behavior of context-aware applications, QoC is essential to contribute to both the effectiveness and the efficiency of such context managers.
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