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Live Migration Control Method for Ensuring Sustainable Development of e-Learning Environment

  • Satoshi Togawa
  • Kazuhide Kanenishi
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 876)

Abstract

In this research, we have generated a method how to control the live-migration destination for disaster risk reduction and disaster recovery framework. This framework is designed for e-Learning environment, it is organized private cloud fabrics, and public cloud services. Grasped disaster warning via smartphone becomes the trigger for data and system protection activity. The framework makes live-migration operation between private cloud fabrics and public cloud services. When the cloud fabrics are affected by any kind of crises, the educational environments which are operated on affected cloud fabric is to be migrate to the safest cloud fabric. And the safest cloud fabric which is targeted for live-migration destination is selected by control algorithm. In this paper, we show our proposed disaster risk reduction framework, and we describe proposed control method to select live-migration destination using crisis alerts. Then, we show the experimental results on the prototype system.

Keywords

e-Learning infrastructure Hybrid cloud Risk management Disaster risk reduction Disaster recovery Earthquake early warning 

Notes

Acknowledgments

This work was supported by JSPS KAKENHI Grants Number 18K02922.

References

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    Fire and Disaster Management Agency Japan: The 2014 White Paper on Fire Service. http://www.fdma.go.jp/html/hakusho/h26/h26/index3.html
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    Togawa, S., Kanenishi, K.: Disaster recovery framework for e-Learning environment using hybrid cloud computing and crisis alert. In: Proceedings of 10th International Conference of Education, Research and Innovation, pp. 5672–5677 (2017)Google Scholar
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    3GPP TS 23.041 V15.1.0: 3rd Generation Partnership Project (3GPP): Technical Specification Group Core Network and Terminals; Technical realization of Cell Broadcast Service (2018)Google Scholar
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    Japan Meteorological Agency: Automated Meteorological Data Acquisition System. http://www.jma.go.jp/jma/kishou/know/amedas/kaisetsu.html

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.Education Center for Information ProcessingShikoku UniversityTokushimaJapan
  2. 2.Center of University Education, Tokushima UniversityTokushimaJapan

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