Study on Grid-Based Special Remotely Sensed Data Processing Node in Grid GIS
Grid Geospatial Information Service (Grid GIS) system aims to study and develop grid-based uniform spatial information access and analysis system. Data resources of Grid GIS include not only original and traditional GIS data but remotely sensed data. Everyday, space missions involve the download, from space to ground, of huge amount of raw images that are stored in the ground stations geographically distributed. It is a practical pressing task to process these data resource in real time or almost real time and to effectively share spatial information among remote sensing community. Grid technology can provide access to a global distributed computing environment via authentication, authorization, negotiation and security tools. This paper discusses the key technologies of Grid-based special remotely sensed data processing node. First, the concept of Grid-based special remotely sensed data processing node is introduced. Following is the architecture and functions of this node. Based on this architecture, the tasks scheduling algorithm is presented. Finally we introduce the computing resource meta-module information registry and renewal mechanism of the Grid-based special remotely sensed data processing node for Grid GIS.
KeywordsGrid Environment Virtual Resource Grid Technology Globus Toolkit Task Scheduler
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- Foster, I., Kesselman, C. (eds.): The Grid: Blueprint for a New Computing Infrastructure. Morgan Kaufmann, San Francisco (1999)Google Scholar
- Foster, I.C., Kesselman, S.: Tuecke The Anatomy of the Grid. Intl J. Supercomputer Applications (2001)Google Scholar
- Johnston, W.E., Gannon, D., Nitzberg, B., Tanner, L.A., Thigpen, B., Woo, A.: Computing and Data Grids for Science and Engineering (2004), http://www.sc2000.org/techpapr/papers/pap.pap253.pdf
- Petrie, G.M., Dippold, C., Fann, G., Jones, D., Jurrus, E., Moon, B., Perrine, K.: Distributed Computing Approach for Remote Sensing Data. In: Proceedings of the International Parallel and Distributed Processing Symposium (IPDPS 2003), Nice, France, April 22-26 (2003)Google Scholar