A hybrid cloud computing approach for managing spatial data: a case study for water resources in Greece

Dimitrios Kallergis, Chrysoula Papacharalampou, Konstantinos Chimos, Thomas Chavakis, Christos Douligeris

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Global challenges and technology advancements have driven researchers and professionals to demand new tools for solving complex problems in terms of massive data exploitation. This paper describes a system that offers 3D visualisation of data with spatial interest regarding the management of water resources. The Software as a Service (SaaS) delivery is instrumented by a hybrid cloud implementation. A public cloud is used for a web service that accommodates the database system and the network traffic load provisioning, whilst a private cloud serves the rest of the web service, along with a custom metering service regarding the hybrid cloud's overall performance. In the context of this work, the geospatial data are exploited similarly to those which will be offered by governmental authorities in Greece conforming to European and National Laws and provide Web Mapping Services through open-access data repositories. Since these data storage solutions are still in an on-going progress, this paper works with private data gathered from professionals in the field of Earth Sciences. The resulted service provides seamless access to the geospatial data which are presented in a 3D web platform.
Original languageEnglish
Title of host publication5th International Conference on Computing for Geospatial Research and Application
PublisherIEEE
ISBN (Electronic)9781479943210
DOIs
Publication statusPublished - 4 Aug 2014

Keywords

  • cloud computing
  • water resources
  • spatial analysis

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    Kallergis, D., Papacharalampou, C., Chimos, K., Chavakis, T., & Douligeris, C. (2014). A hybrid cloud computing approach for managing spatial data: a case study for water resources in Greece. In 5th International Conference on Computing for Geospatial Research and Application IEEE. https://doi.org/10.1109/COM.Geo.2014.18