Towards a framework for High Performance Geocomputation: Handling Vector Topology within a Distributed Service Environment

This paper lays out a framework, based on the emerging Open GIS standards, which will allow the integration of parallel computing technology such that it becomes a viable component of a new generation of geographical information system (GIS) software. The significant costs of parallel re-implementation have thus far acted as a major disincentive to software vendors taking advantage of parallel technology to solve performance problems. These problems will be thrown into sharp focus by the demands of web-based geographical information services. Designs for a series of software libraries, which are subject to a prototype implementation involving the use of a sophisticated data format (Neutral Transfer Format Level 4), are examined with a view to re-implementation making use of the Open GIS Abstract Specification Model. A range of services are envisaged, which can provide functions at various levels from data retrieval, spatial analysis and map generation to specialist environmental models, which are made available over the Internet. Parallelism is seen as an important route for accelerating individual transactions. These services can equally be based on large specialised parallel servers or a co-operating set of under-used workstations. The implementation strategy involves insulating standard serial algorithms from parallelism through support libraries. These libraries handle, for example, the decomposition of the data, thus effectively encapsulating the parallelism within one component of the software and allowing the creation of high-performance software components which are compatible with the Open GIS service architecture.

[1]  Richard Healey,et al.  Parallel Processing Algorithms for GIS , 1997 .

[2]  Steve Dowers,et al.  Parallel processing for geographical applications: A layered approach , 1999, J. Geogr. Syst..

[3]  Ronald Curtis Barrett,et al.  A scan conversion algorithm with reduced storage requirements , 1973, CACM.

[4]  Linda Lilburne,et al.  GIS, expert systems, and interoperability , 1997, Trans. GIS.

[5]  Michael Ian Shamos,et al.  Computational geometry: an introduction , 1985 .

[6]  A. S. Trew,et al.  CHIMP and PUL: Support for portable parallel computing , 1995, Future Gener. Comput. Syst..

[7]  David W. Capson An improved algorithm for the sequential extraction of boundaries from a raster scan , 1984, Comput. Vis. Graph. Image Process..

[8]  Greg Wilson,et al.  Past, Present, Parallel , 1991, Springer London.

[9]  Robert Bernecky,et al.  Book review: Past, Present, Parallel: A Survey of Available Parallel Computing Systems by Arthur Trew & Greg Wilson (Eds.), (Springer-Verlag 1991) , 1991, CARN.

[10]  R. Dixon Raster to vector conversion , 1993 .

[11]  Marc P. Armstrong,et al.  Local Interpolation Using a Distributed Parallel Supercomputer , 1996, Int. J. Geogr. Inf. Sci..

[12]  Andrej Včkovski Interoperable and distributed processing in GIS , 1998 .

[13]  James E. Mower Developing Parallel Procedures for Line Simplification , 1996, Int. J. Geogr. Inf. Sci..

[14]  Forum Mpi MPI: A Message-Passing Interface , 1994 .

[15]  Michael F. Worboys,et al.  Semantic heterogeneity in distributed geographic databases , 1991, SGMD.

[16]  Edith Au,et al.  The Geospatial Interoperability Problem: Lessons Learned from Building the Geolens Prototypye , 1999 .