Scientific and Statistical Database Management, International Conference on (2006)
July 3, 2006 to July 5, 2006
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SSDBM.2006.12
Carlos Rueda , University of California at Davis
Michael Gertz , University of California at Davis
Bertram Ludascher , University of California at Davis
Bernd Hamann , University of California at Davis
Although the processing of data streams has been the focus of many research efforts in several areas, the case of remotely sensed streams in scientific contexts has received little attention. We present an extensible architecture to compose streaming image processing pipelines spanning multiple nodes on a network using a scientific workflow approach. This architecture includes (i) a mechanism for stream query dispatching so new streams can be dynamically generated from within individual processing nodes as a result of local or remote requests, and (ii) a mechanism for making the resulting streams externally available. As complete processing image pipelines can be cascaded across multiple interconnected nodes in a dynamic, scientist-driven way, the approach facilitates the reuse of data and the scalability of computations. We demonstrate the advantages of our infrastructure with a toolset of stream operators acting on remotely sensed data streams for realtime change detection.
B. Hamann, C. Rueda, M. Gertz and B. Ludascher, "An Extensible Infrastructure for Processing Distributed Geospatial Data Streams," 18th International Conference on Scientific and Statistical Database Management(SSDBM), Vienna, 2006, pp. 285-290.