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Article
An Elastic Hybrid Sensing Platform: Architecture and Research Challenges
Procedia Computer Science
  • Sleiman Rabah, Concordia University
  • Fatna Belqasmi, Zayed University
  • Rabeb Mizouni, Khalifa University of Science and Technology
  • Rachida Dssouli, Concordia University
Document Type
Conference Proceeding
Publication Date
1-1-2016
Abstract

© 2016 Published by Elsevier B.V. The dynamic provisioning of hybrid sensing services that integrates both WSN and MPS is a promising, yet challenging concept. It does not only widen the spatial sensing coverage, but it also enables different types of sensing nodes to collaboratively perform sensing tasks and complement each other. Furthermore, it allows for the provisioning of a new category of services that was not possible to implement in pure WSN or MPS networks. Offering a hybrid sensing platform as a service results in several benefits including, but no limited to, efficient sharing and dynamic management of sensing nodes, diversification and reuse of sensing services, as well as combination of many sensing paradigms to enable data to be collected from different sources. However, many challenges need to be resolved before such architecture can be feasible. Currently, the deployment of sensing applications and services is a costly and complex process, which also lacks automation. This paper motivates the need for hybrid sensing, sketches an early architecture, and identifies the research issues with few hints on how to solve them. We argue that a sensing platform that reuses the virtualization and cloud computing concepts will help in addressing many of these challenges, and overcome the limitations of today's deployment practices.

Publisher
Elsevier B.V.
Disciplines
Keywords
  • Dynamic Provisioning,
  • Integration,
  • Mobile Phone Sensing,
  • WSNs
Scopus ID

84985930001

Creative Commons License
Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International
Indexed in Scopus
Yes
Open Access
Yes
Open Access Type
Gold: This publication is openly available in an open access journal/series
Citation Information
Sleiman Rabah, Fatna Belqasmi, Rabeb Mizouni and Rachida Dssouli. "An Elastic Hybrid Sensing Platform: Architecture and Research Challenges" Procedia Computer Science Vol. 94 (2016) p. 113 - 120 ISSN: <p><a href="https://v2.sherpa.ac.uk/id/publication/issn/1877-0509" target="_blank">1877-0509</a></p>
Available at: http://works.bepress.com/fatna-belqasmi/28/