Applications of spatial data structures: Computer graphics, image processing, and GIS
Applications of spatial data structures: Computer graphics, image processing, and GIS
The design and analysis of spatial data structures
The design and analysis of spatial data structures
Introduction to algorithms
Massively parallel strategies for local spatial interpolation
Computers & Geosciences
Communications of the ACM
The grid: blueprint for a new computing infrastructure
The grid: blueprint for a new computing infrastructure
The Quadtree and Related Hierarchical Data Structures
ACM Computing Surveys (CSUR)
Intelligent Optimisation Techniques: Genetic Algorithms, Tabu Search, Simulated Annealing and Neural Networks
A Resource Management Architecture for Metacomputing Systems
IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
The Globus Project: A Status Report
HCW '98 Proceedings of the Seventh Heterogeneous Computing Workshop
A theoretical approach to the use of cyberinfrastructure in geographical analysis
International Journal of Geographical Information Science
International Journal of Geographical Information Science - Distributed Geographic Information Processing Research
TeraGrid GIScience Gateway: Bridging cyberinfrastructure and GIScience
International Journal of Geographical Information Science - Distributed Geographic Information Processing Research
SimpleGrid toolkit: Enabling geosciences gateways to cyberinfrastructure
Computers & Geosciences
System design and implementation of digital-image processing using computational grids
Computers & Geosciences
A MapReduce approach to Gi*(d) spatial statistic
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
A distributed resource broker for spatial middleware using adaptive space-filling curve
Proceedings of the ACM SIGSPATIAL International Workshop on High Performance and Distributed Geographic Information Systems
Proceedings of the 2011 TeraGrid Conference: Extreme Digital Discovery
Spherical interpolation over graphic processing units
Proceedings of the ACM SIGSPATIAL Second International Workshop on High Performance and Distributed Geographic Information Systems
GeoComputation in the grid computing age
W2GIS'06 Proceedings of the 6th international conference on Web and Wireless Geographical Information Systems
Data-Parallel method for georeferencing of MODIS level 1b data using grid computing
ICCS'05 Proceedings of the 5th international conference on Computational Science - Volume Part III
Efficient and validated simulation of crowds for an evacuation assistant
Computer Animation and Virtual Worlds
Journal of Computer Science and Technology - Special issue on Natural Language Processing
Runtime optimisation approaches for a real-time evacuation assistant
PPAM'11 Proceedings of the 9th international conference on Parallel Processing and Applied Mathematics - Volume Part I
Real-time spatial interpolation of continuous phenomena using mobile sensor data streams
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
Accelerating universal Kriging interpolation algorithm using CUDA-enabled GPU
Computers & Geosciences
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Spatial interpolation is widely used in geographical information systems to create continuous surfaces from discrete data points. The creation of such surfaces, however, can involve considerable computation, especially when large problems are addressed, because of the need to search for neighbors on which to base interpolation calculations. Computational Grids provide the computing resources to tackle spatial interpolation in a timely way. The objective of this paper is to investigate the use of domain decomposition for a distributed inverse-distance-weighted spatial interpolation algorithm; the algorithm runs using the Globus Toolkit (GT) in a heterogeneous Grid computing environment. The interpolation algorithm is modified for implementation in the Grid by using a quadtree to spatially index and adaptively decompose the interpolation problem to balance processing loads. In addition, the GT allows the distributed algorithm to couple multiple machines, potentially of different architectures, to dynamically schedule the decomposed sub-problems through Globus services and protocols (e.g., resource management, data transfer). Experiments are conducted to test how well this distributed IDW interpolation algorithm scales to heterogeneous grid computing environments using irregularly distributed geographical data sets.