High-resolution climate and weather forecast models, and regional and global sensor networks, are producing ever-larger quantities of multidimensional environmental data. To be useful, this data must be stored, managed, and made available to a global community of researchers, policymakers, and others. The usual approach to addressing these problems is to operate dedicated data storage and distribution facilities. For example, the Earth System Grid (ESG) (Bernholdt et al., 2005) comprises data systems at several US laboratories, each with large quantities of storage and a high-end server configured to support requests from many remote users. Distributed services such as replica and metadata catalogs integrate these different components into a single distributed system.
Using hybrid grid/cloud computing technologies for environmental data elastic storage, processing and provisioning
Montella Raffaele
;
2010-01-01
Abstract
High-resolution climate and weather forecast models, and regional and global sensor networks, are producing ever-larger quantities of multidimensional environmental data. To be useful, this data must be stored, managed, and made available to a global community of researchers, policymakers, and others. The usual approach to addressing these problems is to operate dedicated data storage and distribution facilities. For example, the Earth System Grid (ESG) (Bernholdt et al., 2005) comprises data systems at several US laboratories, each with large quantities of storage and a high-end server configured to support requests from many remote users. Distributed services such as replica and metadata catalogs integrate these different components into a single distributed system.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
