Share Email Print
cover

Proceedings Paper

On optimal mapping of visualization pipeline onto linear arrangement of network nodes
Author(s): Mengxia Zhu; Qishi Wu; Nageswara S. V. Rao; S. Sitharama Iyengar
Format Member Price Non-Member Price
PDF $14.40 $18.00

Paper Abstract

This paper discusses algorithmic and implementation issues of optimally mapping a visualization pipeline onto a linear arrangement of wide-area network nodes to minimize the total delay. The first network node typically is a data source, the last node could be a display device ranging from a personal computer to a powerwall, and each intermediate node could be a workstation or computational cluster. This mapping scheme appropriately distributes the filtering, geometry generation, rendering, and display modules of the visualization pipeline among various network nodes to make efficient use of the computing resources at end nodes and also the network bandwidth between them. We present an analytical formulation of this problem by taking into account the computational speeds of nodes, bandwidths between them, and the sizes of messages exchanged between the visualization modules. We present polynomial-time optimal algorithms using the dynamic programming method to compute the mappings with minimum total delays for two cases. We implemented an OpenGL-based remote visualization system and deployed it at three geographically distributed nodes. By utilizing bandwidth estimation modules, we implemented and tested the proposed mapping scheme to evaluate both the network transport and computational performance.

Paper Details

Date Published: 11 March 2005
PDF: 11 pages
Proc. SPIE 5669, Visualization and Data Analysis 2005, (11 March 2005); doi: 10.1117/12.587964
Show Author Affiliations
Mengxia Zhu, Louisiana State Univ. (United States)
Qishi Wu, Oak Ridge National Lab. (United States)
Nageswara S. V. Rao, Oak Ridge National Lab. (United States)
S. Sitharama Iyengar, Louisiana State Univ. (United States)


Published in SPIE Proceedings Vol. 5669:
Visualization and Data Analysis 2005
Robert F. Erbacher; Jonathan C. Roberts; Matti T. Grohn; Katy Borner, Editor(s)

© SPIE. Terms of Use
Back to Top