Parallel Distributed Application Framework for Earth Science Data Processing

The management and the processing of Earth science data has been gaining importance over the last decade due to higher data volumes generated by a larger number of instruments and ground stations, and due to the increase in complexity of Earth science models. In order to take full advantage of the vast amount of available data, we need the ability to seamlessly merge data from different sources within the models, and we must be able to process this data in an efficient and timely manner. In order to support these goals, we are developing the Java Distributed Application Framework (JDAF) - a flexible and extensible framework that simplifies the design and implementation of Earth science processing systems. In order to achieve better performance and resource utilization, we parallelize some of the Earth science algorithms within the framework.

• Type: Conference
• Year: 2003
• Where: SCANGIS
• Authors: Petr Votava, Rama Nemani, Keith Golden, Daniel E. Cooke, Hector Hernandez, Changming Ma
• Keywords: Earth Science, Earth Science Data, Earth Science Models, Information Technology, SCANGIS 2003