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Issue No.02 - March/April (2008 vol.14)
pp: 302-312
ABSTRACT
We present a novel approach for latency-tolerant delivery of visualization and rendering results where client-side frame rate display performance is independent of source dataset size, image size, visualization technique or rendering complexity. Our approach delivers pre-rendered, multiresolution images to a remote user as they navigate through different viewpoints, visualization or rendering parameters. We employ demand-driven tiled, multiresolution image streaming and prefetching to efficiently utilize available bandwidth while providing the maximum resolution user can perceive from a given viewpoint. Since image data is the only input to our system, our approach is generally applicable to all visualization and graphics rendering applications capable of generating image files in an ordered fashion. In our implementation, a normal web server provides on-demand images to a remote custom client application, which uses client-pull to obtain and cache only those images required to fulfill the interaction needs. The main contributions of this work are: (1) an architecture for latency-tolerant, remote delivery of precomputed imagery suitable for use with any visualization or rendering application capable of producing images in an ordered fashion; (2) a performance study showing the impact of diverse network environments and different tunable system parameters on end-to-end system performance in terms of deliverable frames per second.
INDEX TERMS
Visualization systems and software, Evolving Internet applications, Distributed/network graphics
CITATION
Jerry Chen, Ilmi Yoon, Wes Bethel, "Interactive, Internet Delivery of Visualization via Structured Prerendered Multiresolution Imagery", IEEE Transactions on Visualization & Computer Graphics, vol.14, no. 2, pp. 302-312, March/April 2008, doi:10.1109/TVCG.2007.70428
REFERENCES
[1] W. Allcock, J. Bresnahan, R. Kettimuthu, and M. Link, “The Globus Striped GridFTP Framework and Server,” Proc. ACM/IEEE Conf. Supercomputing (SC '05), 2005.
[2] M. Beck, T. Moore, and J.S. Plank, “An End-to-End Approach to Globally Scalable Network Storage,” Proc. ACM SIGCOMM '02, pp. 339-346, 2002.
[3] W. Bethel, B. Tierney, J. Lee, D. Gunter, and S. Lau, “Using High-Speed WANs and Network Data Caches to Enable Remote and Distributed Visualization,” Proc. ACM/IEEE Conf. Supercomputing (Supercomputing '00), CDROM, 2000.
[4] I. Bowman, J. Shalf, K.-L. Ma, and E.W. Bethel, “Performance Modeling for 3D Visualization in a Heterogenous Computing Environment,” Technical Report LBNL-56977, Lawrence Berkeley Nat'l Laboratory, Visualization Group, 2004.
[5] D.M. Butler, J.C. Almond, R. Daniel Bergeron, K.W. Brodlie, and R.B. Haber, “Visualization Reference Models,” Proc. Fourth Conf. Visualization (VIS '93), pp. 337-342, 1993.
[6] J. Chen, E.W. Bethel, and I. Yoon, “Interactive, Internet Delivery of Scientific Visualization via Structured, Prerendered Imagery,” Proc. SPIE/IS&T Conf. Electronic Imaging, vol. 6061, pp. A 1-A 10, 2006.
[7] S.E. Chen, “QuickTime VR—An Image-Based Approach to Virtual Environment Navigation,” Computer Graphics, Ann. Conf. Series, vol. 29, pp. 29-38, 1995.
[8] D. Cohen-Or and E. Zadicario, “Visibility Streaming for Network-Based Walkthroughs,” Graphics Interface, pp. 1-7, 1998.
[9] R3vis Corp., OpenRM Scene Graph, http:/www.openrm.org, 1999-2006.
[10] D.R. Commander VirtualGL, http:/www.virtualgl.org, 2007.
[11] D. Ellsworth, C. Henze, B. Green, P. Moran, and T. Sandstrom, “Concurrent Visualization in a Production Supercomputer Environment,” IEEE Trans. Visualization and Computer Graphics, vol. 12, no. 5, pp. 997-1004, Sept.-Oct. 2006.
[12] K. Engel, O. Sommer, C. Ernst, and T. Ertl, “Remote 3D Visualization Using Image-Streaming Techniques,” Proc. Advances in Intelligent Computing and Multimedia Systems (ISIMADE '99), pp.91-96, 1999.
[13] Google Inc., Google Earth, http:/earth.google.com/, 2008.
[14] Google Inc., Google Map, http:/maps.google.com/, 2008.
[15] GUP Linz Inst. of Graphics and Parallel Processing, GVid Project Page, http://www.gup.uni-linz.ac.atgvid/, 2007.
[16] T. Hacker, B. Noble, and B. Athey, “Improving Throughput and Maintaining Fairness Using Parallel TCP,” Proc. IEEE INFOCOM, 2004.
[17] B. Hamann, E.W. Bethel, H. Simon, and J. Meza, “Visualization Greenbook: Future Visualization Needs of the DOE Computational Science Community Hosted at NERSC,” Int'l J. High Performance Computing Applications, vol. 17, no. 2, pp. 97-124, 2003.
[18] H. Hege, A. Hutanu, R. Kähler, A. Merzky, T. Radke, E. Seidel, and B. Ullmer, “Progressive Retrieval and Hierarchical Visualization of Large Remote Data,” Proc. Workshop Adaptive Grid Middleware, Sept. 2003.
[19] H.-C. Hege, A. Merzky, and S. Zachow, “Distributed Visualization with OpenGL VizServer: Practical Experiences,” ZIB Preprint 00-31, 2001.
[20] P. Heinzlreiter and D. Kranzlmüller, “Visualization Services on the Grid: The Grid Visualization Kernel,” Parallel Processing Letters, vol. 13, no. 2, pp. 135-148, 2003.
[21] V. Jacobson, R. Braden, and D. Borman, TCP Extensions for High Performance, IETF RFC 1323, May 1993.
[22] Kitware, Inc. and Jim Ahrens, ParaView: Parallel Visualization Application, http:/www.paraview.org/, 2007.
[23] D. Kranzlmüller, G. Kurka, P. Heinzlreiter, and J. Volkert, “Optimizations in the Grid Visualization Kernel,” Proc. IEEE Parallel and Distributed Processing Symp., CDROM, pp. 129-135, 2002.
[24] Lawrence Livermore Nat'l Laboratory, VisIt: Visualize It Parallel Visualization Application, http://www.llnl.govvisit/, 2007.
[25] E.J. Luke and C.D. Hansen, “Semotus Visum: A Flexible Remote Visualization Framework,” Proc. Conf. Visualization (VIS '02), pp.61-68, 2002.
[26] C. Maxwell, R. Kim, T. Gaskins, F. Kuehnel, and P. Hogan NASA's World Wind, http:/worldwind.arc.nasa.gov/, 2007.
[27] B. McCormick, T. DeFanti, and M. Brown, “Visualization in Scientific Computing,” Computer Graphics, vol. 21, no. 6, Nov. 1987.
[28] V. Pascucci and R.J. Frank, “Global Static Indexing for Real-Time Exploration of Very Large Regular Grids,” Proc. ACM/IEEE Conf. Supercomputing (Supercomputing '01), CDROM, 2001.
[29] S. Prohaska, A. Hutanu, R. Kahler, and H.-C. Hege, “Interactive Exploration of Large Remote Micro-CT Scans,” Proc. Conf. Visualization (VIS '04), pp. 345-352, 2004.
[30] T. Richardson, Q. Stafford-Fraser, K.R. Wood, and A. Hopper, “Virtual Network Computing,” IEEE Internet Computing, vol. 2, no. 1, pp. 33-38, 1998.
[31] J. Rohlf and J. Helman, “IRIS Performer: A High Performance Multiprocessing Toolkit for Real-Time 3D Graphics,” Proc. ACM SIGGRAPH '94, pp. 381-394, 1994.
[32] D.C. Schmidt and T. Suda, “Transport System Architecture Services for High-Performance Communications Systems,” IEEE J. Selected Areas in Comm., vol. 11, no. 4, pp. 489-506, 1993.
[33] Silicon Graphics Inc., OpenGL Vizserver, http://www.sgi.com/products/softwarevizserver /, 2007.
[34] IND Networking Performance Team, NetPerf, http://www.netperf.org/netperfNetperfPage.html , 2007.
[35] I. Yoon and U. Neumann, “IBRAC: Image-Based Rendering Acceleration and Compression,” Proc. Eurographics '00, vol. 19, pp. 321-330, 2000.
[36] Zoomify Inc., Zoomifyer, http:/www.zoomify.com/, 2007.
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