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Adaptive and efficient transfer for online remote visualization of critical weather applications

Malakar, P and Natarajan, V and Vadhiyar, SS (2020) Adaptive and efficient transfer for online remote visualization of critical weather applications. In: 20th International Conference on Computational Science, 3-5, June 2020, Netherlands, pp. 674-693.

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Official URL: https://dx.doi.org/10.1007/978-3-030-50417-5_50


Critical weather applications such as cyclone tracking require online visualization simultaneously performed with the simulations so that the scientists can provide real-time guidance to decision makers. However, resource constraints such as slow networks can hinder online remote visualization. In this work, we have developed an adaptive framework for efficient online remote visualization of critical weather applications. We present three algorithms, namely, most-recent, auto-clustering and adaptive, for reducing lag between the simulation and visualization times. Using experiments with different network configurations, we find that the adaptive algorithm strikes a good balance in providing reduced lags and visualizing most representative frames, with up to 72 smaller lag than auto-clustering, and 37 more representative than most-recent for slow networks.

Item Type: Conference Paper
Publication: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Publisher: Springer
Additional Information: The copyright of this article belongs to Springer
Keywords: Adaptive algorithms; Decision making; Storms, Adaptive framework; Cyclone tracking; Decision makers; Network configuration; Online visualizations; Remote visualization; Resource Constraint; Simulation and visualizations, Visualization
Department/Centre: Division of Interdisciplinary Sciences > Computational and Data Sciences
Date Deposited: 24 Aug 2020 05:56
Last Modified: 24 Aug 2020 05:56
URI: http://eprints.iisc.ac.in/id/eprint/66192

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