Virtual telemetry for dynamic data-driven application simulations

Authors:
Craig C. Douglas;Yalchin Efendiev;Richard Ewing;Raytcho Lazarov;Martin J. Cole;Greg Jones;Chris R. Johnson
Affiliations:
University of Kentucky, Department of Computer Science, Lexington, KY and Yale University, Department of Computer Science, CT;Texas A&M University, College Station, TX;Texas A&M University, College Station, TX;Texas A&M University, College Station, TX;Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT;Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT;Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT
Venue:
ICCS'03 Proceedings of the 2003 international conference on Computational science
Year:
2003

Citing 2
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Abstract

We describe a virtual telemetry system that allows us to devise and augment dynamic data-driven application simulations (DDDAS). Virtual telemetry has the advantage that it is inexpensive to produce from real time simulations and readily transmittable using open source streaming software. Real telemetry is usually expensive to receive (if it is even available long term), tends to be messy, comes in no particular order, and can be incomplete or erroneous due to transmission problems or sensor malfunction. We will generate multiple streams continuously for extended periods (e.g., months or years): clean data, somewhat error prone data, and quite lossy or inaccurate data. By studying all of the streams at once we will be able to devise DDDAS components useful in predictive contaminant modeling.