Virtual Telemetry for Dynamic Data-Driven Application Simulations

Craig C. Douglas1,2, Yalchin Efendiev3, Richard Ewing3, Raytcho Lazarov3, Martin J. Cole4, Greg Jones4, Chris R. Johnson4

1University of Kentucky, Department of Computer Science, 325 McVey Hall, Lexington, KY 40506-0045, USA
craig.douglas@uky.edu

2Yale University, Department of Computer Science, P.O.Box 208285, New Haven, CT 06520-8285,USA
douglas_craig@cs.yale.edu

3Texas A&M University, College Station, TX, USA
efendiev@math.tamu.ed
lazarov@math.tamu.ed
richard_ewing@tamu.edu

4Scientific Computing and Imaging Institute, University of Utah, Salt Lake City, UT, USA
mjc@sci.utah.edu
crj@cs.utah.edu

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 longterm), 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.

LNCS 2660, pp. 279-288.

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