Feasibility Study and Experience on Using Cloud Infrastructure and Platform for Scientific Computing

  • Mikael Fernandus Simalango
  • Sangyoon Oh


In the academia, conducting experiments, gathering and processing data are trivial tasks. However, in some circumstances for example when processing large-set of data, method to accomplish the task can be tricky and non-trivial, not to mention problematic. When it comes to numerical float or array, processing a very large set of this kind of data will require superior computing power. Some entities with splendid compute nodes may process the data directly in their own infrastructure. Yet, providing decent infrastructure for processing large data sets or resource-extensive task can be a challenge for other entities. Infrastructure owned by an entity conducting the computation can be insufficient or just enough to execute the tasks above the minimum requirements. A common practice for infrastructure-limited research entity in dealing with such kind of situation is to outsource the compute task to external party with more superior compute power in order to reduce waiting time for producing the result of data processing.


Cloud Computing Cloud Service Public Cloud Cloud Infrastructure Private Cloud 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  1. 1.WISE Research LabAjou UniversitySuwonSouth Korea
  2. 2.WISE Research Lab, School of Information and Communication EngineeringAjou UniversitySuwonSouth Korea

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