VASA: Interactive computational steering of large asynchronous simulation pipelines for societal infrastructure

Sungahn Ko, Jieqiong Zhao, Jing Xia, Shehzad Afzal, Xiaoyu Wang, Greg Abram, Niklas Elmqvist, Len Kne, David C Van Riper, Kelly Gaither, Shaun Kennedy, William Tolone, William Ribarsky, David S. Ebert

Research output: Contribution to journalArticlepeer-review

14 Scopus citations


(Figure Presented) We present VASA, a visual analytics platform consisting of a desktop application, a component model, and a suite of distributed simulation components for modeling the impact of societal threats such as weather, food contamination, and traffic on critical infrastructure such as supply chains, road networks, and power grids. Each component encapsulates a high-fidelity simulation model that together form an asynchronous simulation pipeline: a system of systems of individual simulations with a common data and parameter exchange format. At the heart of VASA is theWorkbench, a visual analytics application providing three distinct features: (1) low-fidelity approximations of the distributed simulation components using local simulation proxies to enable analysts to interactively configure a simulation run; (2) computational steering mechanisms to manage the execution of individual simulation components; and (3) spatiotemporal and interactive methods to explore the combined results of a simulation run. We showcase the utility of the platform using examples involving supply chains during a hurricane as well as food contamination in a fast food restaurant chain.

Original languageEnglish (US)
Article number6875926
Pages (from-to)1853-1862
Number of pages10
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number12
StatePublished - Dec 31 2014

Bibliographical note

Publisher Copyright:
© 2014 IEEE.


  • Computational steering
  • Critical infrastructure
  • Homeland security
  • Visual analytics


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