Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4950130 | Future Generation Computer Systems | 2017 | 36 Pages |
Abstract
The current proposals of hybrid context modeling bring new challenges, an important one is how applications can access and process data stored on these models. Thinking about that, this paper proposes a solution to deal with this challenge through a compositional approach that explores the context information on hybrid models, called EXEHDA-HM. The proposed approach stands out by the design of a repository that supports three database models and by the compositional processing strategy based on rules. In our proposal, the applications can combine data stored on different bases in a single rule, which could enhance the identification of contextual situations. For the evaluation we designed and implemented some case studies on information security area, exploring the hybrid repository composed of relational, non-relational, and triple storage models. Our results demonstrate that was possible to identify richer situations with the data composition across more than one model and there are situations that can only be found through this composition.
Related Topics
Physical Sciences and Engineering
Computer Science
Computational Theory and Mathematics
Authors
Roger da Silva Machado, Ricardo Borges Almeida, Diórgenes Yuri Leal da Rosa, João Ladislau Barbará Lopes, Ana Marilza Pernas, Adenauer Corrêa Yamin,