Dynamic Real-Time Infrastructure Planning and Deployment for Disaster Early Warning Systems

Authors
Publication date 2018
Host editors
  • Y. Shi
  • H. Fu
  • Y. Tian
  • V.V. Krzhizhanovskaya
  • M.H. Lees
  • J. Dongarra
  • P.M.A. Sloot
Book title Computational Science – ICCS 2018
Book subtitle 18th International Conference, Wuxi, China, June 11–13, 2018 : proceedings
ISBN
  • 9783319937007
ISBN (electronic)
  • 9783319937014
Series Lecture Notes in Computer Science
Event 18th International Conference on Computational Science, ICCS 2018
Volume | Issue number 2
Pages (from-to) 644-654
Number of pages 11
Publisher Cham: Springer
Organisations
  • Faculty of Science (FNWI) - Informatics Institute (IVI)
  • Faculty of Science (FNWI)
Abstract
An effective nature disaster early warning system often relies on widely deployed sensors, simulation based predicting components, and a decision making system. In many cases, the simulation components require advanced infrastructures such as Cloud for performing the computing tasks. However, effectively customizing the virtualized infrastructure from Cloud based time critical constraints and locations of the sensors, and scaling it based on dynamic loads of the computation at runtime is still difficult. The suitability of a Dynamic Real-time Infrastructure Planner (DRIP) that handles the provisioning within cloud environments of the virtual infrastructure for time-critical applications is demonstrated with respect to disaster early warning systems. The DRIP system is part of the SWITCH project (Software Workbench for Interactive, Time Critical and Highly self-adaptive Cloud applications).
Document type Conference contribution
Language English
Published at https://doi.org/10.1007/978-3-319-93701-4_51
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