A multilevel cache model for runtime optimization of remote visualization

Robert Sisneros, Chad Jones, Jian Huang, Jinzhu Gao, Byung Hoon Park, Nagiza F. Samatova

Research output: Contribution to journalArticlepeer-review


Remote visualization is an enabling technology aiming to resolve the barrier of physical distance. Although many researchers have developed innovative algorithms for remote visualization, previous work has focused little on systematically investigating optimal configurations of remote visualization architectures. In this paper, we study caching and prefetching, an important aspect of such architecture design, in order to optimize the fetch time in a remote visualization system. Unlike a processor cache or Web cache, caching for remote visualization is unique and complex. Through actual experimentation and numerical simulation, we have discovered ways to systematically evaluate and search for optimal configurations of remote visualization caches under various scenarios, such as different network speeds, sizes of data for user requests, prefetch schemes, cache depletion schemes, etc. We have also designed a practical infrastructure software to adaptively optimize the caching architecture of general remote visualization systems, when a different application is started or the network condition varies. The lower bound of achievable latency discovered with our approach can aid the design of remote visualization algorithms and the selection of suitable network layouts for a remote visualization system.

Original languageEnglish (US)
Pages (from-to)991-1003
Number of pages13
JournalIEEE Transactions on Visualization and Computer Graphics
Issue number5
StatePublished - Sep 2007
Externally publishedYes


  • Caching
  • Distributed visualization
  • Performance analysis
  • Remote visualization

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Computer Vision and Pattern Recognition
  • Computer Graphics and Computer-Aided Design


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