The Italian GPS receiver for Radio Occultation has been launched from the Satish Dhawan Space Center (Sriharikota, India) on board of the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to develop an innovative solution in order to quickly elaborate RO data and extract atmospherical profiles. The algorithms adopted can be used to characterize the temperature, pressure and humidity. In consideration of large amount of data to process, an hybrid infrastructure has been created using both the existing grid environment (fully physical) and the virtual environment composed of virtual machines from local cloud infrastructure and Amazon EC2. This enhancement of the project stems from the need of computational power in case of an unexpected burst of calculation that the physical infrastructure would not be able to respond on its own. The virtual environment implemented guarantees flexibility and a progressive scalability and other benefits derived by virtualization and cloud computing. © 2013 Springer-Verlag Berlin Heidelberg.

Improving scalability of an hybrid infrastructure for e-science applications / Terzo, O.; Mossucca, L.; Ruiu, P.; Caragnano, G.; Goga, K.; Notarpietro, R.; Cucca, M. (LECTURE NOTES IN ARTIFICIAL INTELLIGENCE). - In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)[s.l] : Springer Verlag, 2013. - ISBN 978-3-642-38495-0. - pp. 120-134 [10.1007/978-3-642-38496-7_8]

Improving scalability of an hybrid infrastructure for e-science applications

Ruiu P.;Notarpietro R.;Cucca M.
2013

Abstract

The Italian GPS receiver for Radio Occultation has been launched from the Satish Dhawan Space Center (Sriharikota, India) on board of the Indian Remote Sensing OCEANSAT-2 satellite. The Italian Space Agency has established a set of Italian universities and research centers to develop an innovative solution in order to quickly elaborate RO data and extract atmospherical profiles. The algorithms adopted can be used to characterize the temperature, pressure and humidity. In consideration of large amount of data to process, an hybrid infrastructure has been created using both the existing grid environment (fully physical) and the virtual environment composed of virtual machines from local cloud infrastructure and Amazon EC2. This enhancement of the project stems from the need of computational power in case of an unexpected burst of calculation that the physical infrastructure would not be able to respond on its own. The virtual environment implemented guarantees flexibility and a progressive scalability and other benefits derived by virtualization and cloud computing. © 2013 Springer-Verlag Berlin Heidelberg.
2013
978-3-642-38495-0
978-3-642-38496-7
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11583/2897116