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Related Experiment Videos

A multi-level cache model for run-time optimization of remote visualization.

Robert Sisneros1, Chad Jones, Jian Huang

  • 1Department of Computer Science, University of Tennessee, Knoxville, TN 37996, USA. sisneros@cs.utk.edu

IEEE Transactions on Visualization and Computer Graphics
|July 12, 2007
PubMed
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This study optimizes remote visualization systems by systematically evaluating caching and prefetching strategies. Our findings provide a lower bound for achievable latency, aiding system design and network layout selection.

Area of Science:

  • Computer Science
  • Information Technology

Background:

  • Remote visualization systems face challenges due to physical distance.
  • Existing research has not systematically investigated optimal remote visualization architectures.

Purpose of the Study:

  • To optimize fetch time in remote visualization systems by studying caching and prefetching.
  • To systematically evaluate and search for optimal configurations of remote visualization caches.

Main Methods:

  • Experimentation and numerical simulation were used to evaluate caching configurations.
  • A practical infrastructure software was designed for adaptive optimization of caching architectures.

Main Results:

  • Identified optimal configurations for remote visualization caches under various network conditions and data sizes.

Related Experiment Videos

  • Developed an adaptive software solution for dynamic optimization of caching architectures.

    • Conclusions:

    • The discovered lower bound of achievable latency can guide the design of remote visualization algorithms.
    • Findings assist in selecting suitable network layouts for remote visualization systems.