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Context-Aware Systems and Applications. 10th EAI International Conference, ICCASA 2021, Virtual Event, October 28–29, 2021, Proceedings

Research Article

Memory-Constrained Context-Aware Reasoning

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  • @INPROCEEDINGS{10.1007/978-3-030-93179-7_11,
        author={Ijaz Uddin and Abdur Rakib and Mumtaz Ali and Phan Cong Vinh},
        title={Memory-Constrained Context-Aware Reasoning},
        proceedings={Context-Aware Systems and Applications. 10th EAI International Conference, ICCASA 2021, Virtual Event,  October 28--29, 2021, Proceedings},
        proceedings_a={ICCASA},
        year={2022},
        month={1},
        keywords={Context-aware systems Rule-based reasoning Working memory},
        doi={10.1007/978-3-030-93179-7_11}
    }
    
  • Ijaz Uddin
    Abdur Rakib
    Mumtaz Ali
    Phan Cong Vinh
    Year: 2022
    Memory-Constrained Context-Aware Reasoning
    ICCASA
    Springer
    DOI: 10.1007/978-3-030-93179-7_11
Ijaz Uddin1, Abdur Rakib2, Mumtaz Ali1, Phan Cong Vinh
  • 1: Department of Computer Science
  • 2: Department of Computer Science and Creative Technologies

Abstract

The context-aware computing paradigm introduces environments, known as smart spaces, which can unobtrusively and proactively assist their users. These systems are currently mostly implemented on mobile platforms considering various techniques, including ontology-driven multi-agent rule-based reasoning. Rule-based reasoning is a relatively simple model that can be adapted to different real-world problems. It can be developed considering a set of assertions, which collectively constitute the working memory, and a set of rules that specify how to act on the assertion set. However, the size of the working memory is crucial when developing context-aware systems in resource constrained devices such as smartphones and wearables. In this paper, we discuss rule-based context-aware systems and techniques for determining the required working memory size for a fixed set of rules.

Keywords
Context-aware systems Rule-based reasoning Working memory
Published
2022-01-06
Appears in
SpringerLink
http://dx.doi.org/10.1007/978-3-030-93179-7_11
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