Flocks, herds and schools: A distributed behavioral model
SIGGRAPH '87 Proceedings of the 14th annual conference on Computer graphics and interactive techniques
The SEQUOIA 2000 storage benchmark
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
The Grid 2: Blueprint for a New Computing Infrastructure
The Grid 2: Blueprint for a New Computing Infrastructure
An autonomic tool for building self-organizing Grid-enabled applications
Future Generation Computer Systems
A general architecture for grid-based PSE toolkits
PARA'04 Proceedings of the 7th international conference on Applied Parallel Computing: state of the Art in Scientific Computing
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Geological data management and mining are critical areas of modern-day geology research. High throughput and high information content are two important aspects of any geoprocessing application. Geological data mining is efficient and faster if the geological data are indexed, stored and mined on content. A challenge for geological information mining is the distributed nature of the resources. Grid computing has emerged as an important new field in the distributed computing arena. It focuses on intensive resource sharing, innovative applications, and in some cases, high performance orientation. This paper describes how Grids technologies can be used to develop an infrastructure for developing geoprocessing applications that use content-based information mining. We present the MOSÈ system, a Grid-enabled problem solving environment (PSE) able to support the activities that concern the mining of geophysical data and modelling and simulation of spatio-temporal phenomena for analyzing and managing the identification and the mitigation of natural disasters like landslides, floods, wildfires, etc. MOSÈ takes advantages of the standardized resource access and workflow support for loosely coupled software components provided by the web/grid services technologies.