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A hybrid architecture to enrich context awareness through data correlation

Published:09 April 2018Publication History

ABSTRACT

Context awareness brings new challenges, and an important one is how applications can manipulate the contextual data stored in more than one model. In this research, we propose HACCD, a context-aware architecture to process information based on hybrid models. HACCD is designed to provide context awareness considering different stages: (i) acquisition of context; (ii) preprocessing stage; (iii) context processing with a hybrid reasoning strategy; (iv) data storage with the support of three database models; (v) repository communication that enable access to contextual information; and, (vi) correlation approach based on compositional rules that allow the combination of data stored in distinct models. To validate our architecture we designed and tested within some scenarios based on information security. The obtained results showed that the possibility of correlating data from different natures could help to identify richer situations, thus improving decision-making.

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  1. A hybrid architecture to enrich context awareness through data correlation

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      cover image ACM Conferences
      SAC '18: Proceedings of the 33rd Annual ACM Symposium on Applied Computing
      April 2018
      2327 pages
      ISBN:9781450351911
      DOI:10.1145/3167132

      Copyright © 2018 Owner/Author

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 9 April 2018

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      Overall Acceptance Rate1,650of6,669submissions,25%

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