VASA: Interactive Computational Steering of Large Asynchronous Simulation Pipelines for Societal Infrastructure
Autor: | David Van Riper, Shaun Kennedy, Len Kne, Shehzad Afzal, Niklas Elmqvist, William J. Tolone, Jieqiong Zhao, Greg Abram, Sungahn Ko, Xiaoyu Wang, Kelly Gaither, William Ribarsky, David S. Ebert, Jing Xia |
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Rok vydání: | 2014 |
Předmět: |
Visual analytics
Informatics Computer science Distributed computing Disaster Planning Transportation Security Measures Critical infrastructure Data modeling Computer graphics Software Component (UML) Computer Graphics Humans Weather Computational steering Simulation System of systems Cyclonic Storms business.industry Models Theoretical Computer Graphics and Computer-Aided Design Pipeline (software) Equipment and Supplies Asynchronous communication Analytics Signal Processing Computer Vision and Pattern Recognition business Power Plants |
Zdroj: | IEEE Transactions on Visualization and Computer Graphics. 20:1853-1862 |
ISSN: | 2160-9306 1077-2626 |
Popis: | 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 the Workbench, 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. |
Databáze: | OpenAIRE |
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