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2014 Volume 29
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RESEARCH ARTICLE   Open Access    

Quality of Context: models and applications for context-aware systems in pervasive environments

  • Institute of Information Systems

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  • Abstract: Limitations of sensors and the situation of a specific measurement can affect the quality of context information that is implicitly collected in pervasive environments. The lack of information about Quality of Context (QoC) can result in degraded performance of context-aware systems in pervasive environments, without knowing the actual problem. Context-aware systems can take advantage of QoC if context producers also provide QoC metrics along with context information. In this paper, we analyze QoC and present our model for processing QoC metrics. We evaluate QoC metrics considering the capabilities of sensors, circumstances of specific measurement, requirements of context consumer, and the situation of the use of context information. We also illustrate how QoC metrics can facilitate in enhancing the effectiveness and efficiency of different tasks performed by a system to provide context information in pervasive environments.
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  • Cite this article

    Atif Manzoor, Hong-Linh Truong, Schahram Dustdar. 2014. Quality of Context: models and applications for context-aware systems in pervasive environments. The Knowledge Engineering Review 29(2)154−170, doi: 10.1017/S0269888914000034
    Atif Manzoor, Hong-Linh Truong, Schahram Dustdar. 2014. Quality of Context: models and applications for context-aware systems in pervasive environments. The Knowledge Engineering Review 29(2)154−170, doi: 10.1017/S0269888914000034
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RESEARCH ARTICLE   Open Access    

Quality of Context: models and applications for context-aware systems in pervasive environments

  • Institute of Information Systems

  • Published online: 21 March 2014
The Knowledge Engineering Review  29,  2014, 29(2): 154−170  |  Cite this article

Abstract: Abstract: Limitations of sensors and the situation of a specific measurement can affect the quality of context information that is implicitly collected in pervasive environments. The lack of information about Quality of Context (QoC) can result in degraded performance of context-aware systems in pervasive environments, without knowing the actual problem. Context-aware systems can take advantage of QoC if context producers also provide QoC metrics along with context information. In this paper, we analyze QoC and present our model for processing QoC metrics. We evaluate QoC metrics considering the capabilities of sensors, circumstances of specific measurement, requirements of context consumer, and the situation of the use of context information. We also illustrate how QoC metrics can facilitate in enhancing the effectiveness and efficiency of different tasks performed by a system to provide context information in pervasive environments.

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    Acknowledgments

    • This research is partially supported by the European Union through the FP6-2005-IST-5-034749 project WORKPAD.

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    Cite this article
    Atif Manzoor, Hong-Linh Truong, Schahram Dustdar. 2014. Quality of Context: models and applications for context-aware systems in pervasive environments. The Knowledge Engineering Review 29(2)154−170, doi: 10.1017/S0269888914000034
    Atif Manzoor, Hong-Linh Truong, Schahram Dustdar. 2014. Quality of Context: models and applications for context-aware systems in pervasive environments. The Knowledge Engineering Review 29(2)154−170, doi: 10.1017/S0269888914000034
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