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In this study, we present a framework based on a prediction model that facilitates user access to a number of services in a smart living environment. Users must be able to access all available services continuously equipped with mobile devices or smart objects without being impacted by technical constraints such as performance or memory issues, regardless of their physical location and mobility. To achieve this goal, we propose the use of cloudlet-based architecture that serves as distributed cloud resources with specific ranges of influence and a real-time processing framework that tracks events and preferences of the end consumers, predicts their requirements, and recommends services to optimize resource utilization and service response time.


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Toward a Real-Time Framework in Cloudlet-Based Architecture

Show Author's information O. Kotevska( )A. LbathS. Bouzefrane
CNRS, LIG, University Grenoble Alpes, Grenoble F-38000, France.
CEDRIC Lab, Conservatoire National des Arts et Metiers CNAM, Paris 75003, France.

Abstract

In this study, we present a framework based on a prediction model that facilitates user access to a number of services in a smart living environment. Users must be able to access all available services continuously equipped with mobile devices or smart objects without being impacted by technical constraints such as performance or memory issues, regardless of their physical location and mobility. To achieve this goal, we propose the use of cloudlet-based architecture that serves as distributed cloud resources with specific ranges of influence and a real-time processing framework that tracks events and preferences of the end consumers, predicts their requirements, and recommends services to optimize resource utilization and service response time.

Keywords: real-time, prediction, smart city, cloudlet, recommendations, framework

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Publication history

Received: 15 September 2015
Accepted: 13 October 2015
Published: 04 February 2016
Issue date: February 2016

Copyright

© The author(s) 2016

Acknowledgements

This work was supported by the National Institute of Standards and Technologies (NIST), and conducted within a collaboration under Information Technology Laboratory, Advanced Network Technologies Division (ANTD) and the Universities of Grenoble and CNAM. Our special thanks go to Dr. Abdella Battou, ANTD division chief for his support and advises.

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