Virtual telemetry for dynamic data-driven application simulations

Craig C. Douglas*, Yalchin Efendiev, Richard Ewing, Raytcho Lazarov, Martin J. Cole, Greg Jones, Chris R. Johnson

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsPeter M. A. Sloot, David Abramson, Alexander V. Bogdanov, Yuriy E. Gorbachev, Jack J. Dongarra, Albert Y. Zomaya
PublisherSpringer Verlag
Pages279-288
Number of pages10
ISBN (Print)3540401970, 9783540401971
DOIs
StatePublished - Jan 1 2003

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume2660
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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