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An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems

Rakib, Abdur; Uddin, Ijaz

Authors

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Rakib Abdur Rakib.Abdur@uwe.ac.uk
Senior Lecturer in Mobile Security

Ijaz Uddin



Abstract

© 2018, The Author(s). Over the last few years, context-aware computing has received a growing amount of attention among the researchers in the IoT and ubiquitous computing community. In principle, context-aware computing transforms a physical environment into a smart space by sensing the surrounding environment and interpreting the situation of the user. This process involves three major steps: context acquisition, context modelling, and context-aware reasoning. Among other approaches, ontology-based context modelling and rule-based context reasoning are widely used techniques to enable semantic interoperability and interpreting user situations. However, implementing rich context-aware applications that perform reasoning on resource-bounded mobile devices is quite challenging. In this paper, we present a context-aware systems development framework for smart spaces, which includes a lightweight efficient rule engine and a wide range of user preferences to reduce the number of rules while inferring personalized contexts. This shows rules can be reduced in order to optimize the inference engine execution speed, and ultimately to reduce total execution time and execution cost.

Citation

Rakib, A., & Uddin, I. (2019). An Efficient Rule-Based Distributed Reasoning Framework for Resource-bounded Systems. Mobile Networks and Applications, 24(1), 82-99. https://doi.org/10.1007/s11036-018-1140-x

Journal Article Type Article
Acceptance Date Sep 23, 2018
Online Publication Date Oct 23, 2018
Publication Date Feb 15, 2019
Journal Mobile Networks and Applications
Print ISSN 1383-469X
Electronic ISSN 1572-8153
Publisher Springer Verlag
Peer Reviewed Peer Reviewed
Volume 24
Issue 1
Pages 82-99
DOI https://doi.org/10.1007/s11036-018-1140-x
Keywords rule-based reasoning, expert systems, preferences, context-aware systems
Public URL https://uwe-repository.worktribe.com/output/851611
Publisher URL https://doi.org/10.1007/s11036-018-1140-x

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