
This Article  
 
Share  
Bibliographic References  
Add to:  
Digg Furl Spurl Blink Simpy Del.icio.us Y!MyWeb  
Search  
 
ASCII Text  x  
Shashi Shekhar, Sivakumar Ravada, Vipin Kumar, Douglas Chubb, Greg Turner, "Declustering and LoadBalancing Methods for Parallelizing Geographic Information Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 4, pp. 632655, July/August, 1998.  
BibTex  x  
@article{ 10.1109/69.706061, author = {Shashi Shekhar and Sivakumar Ravada and Vipin Kumar and Douglas Chubb and Greg Turner}, title = {Declustering and LoadBalancing Methods for Parallelizing Geographic Information Systems}, journal ={IEEE Transactions on Knowledge and Data Engineering}, volume = {10}, number = {4}, issn = {10414347}, year = {1998}, pages = {632655}, doi = {http://doi.ieeecomputersociety.org/10.1109/69.706061}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }  
RefWorks Procite/RefMan/Endnote  x  
TY  JOUR JO  IEEE Transactions on Knowledge and Data Engineering TI  Declustering and LoadBalancing Methods for Parallelizing Geographic Information Systems IS  4 SN  10414347 SP632 EP655 EPD  632655 A1  Shashi Shekhar, A1  Sivakumar Ravada, A1  Vipin Kumar, A1  Douglas Chubb, A1  Greg Turner, PY  1998 KW  Declustering methods KW  geographic information systems KW  high performance KW  loadbalancing KW  polygon clipping KW  range query. VL  10 JA  IEEE Transactions on Knowledge and Data Engineering ER   
Abstract—Declustering and loadbalancing are important issues in designing a highperformance geographic information system (HPGIS), which is a central component of many interactive applications(such as realtime terrain visualization. The current literature provides efficient methods for declustering spatial pointdata. However, there has been little work toward developing efficient declustering methods for collections of extended objects, like chains of linesegments and polygons. In this paper, we focus on the datapartitioning approach to parallelizing GIS operations. We provide a framework for declustering collections of extended spatial objects by identifying the following key issues: 1) the workload metric, 2) the spatialextent of the workload, 3) the distribution of the workload over the spatialextent, and 4) the declustering method. We identify and experimentally evaluate alternatives for each of these issues. In addition, we also provide a framework for dynamically balancing the load between different processors. We experimentally evaluate the proposed declustering and loadbalancing methods on a distributed memory MIMD machine (Cray T3D). Experimental results show that the spatialextent and the workload metric are important issues in developing a declustering method. Experiments also show that the replication of data is usually needed to facilitate dynamic loadbalancing, since the cost of local processing is often less than the cost of data transfer for extended spatial objects. In addition, we also show that the effectiveness of dynamic loadbalancing techniques can be improved by using declustering methods to determine the subsets of spatial objects to be transferred during runtime.
[1] DIS Home Page, http:/dis.pica.army.mil.
[2] A. Aggarwal, B. Chazelle, L. Guibas, C. O'Dunlaing, and C. Yap, "Parallel Computational Geometry," Proc. 25th IEEE Symp. Foundations of Computer Science, pp. 468477, 1985.
[3] S.G. Akl and K.A. Lyons, Parallel Computational Geometry, Prentice Hall, Englewood Cliffs, N.J., 1993.
[4] M.P. Armstrong, C.E. Pavlik, and R. Marciano, "Experiments in the Measurement of Spatial Association Using a Parallel Supercomputer," Geographical Systems, vol. 1, pp. 267288, 1994.
[5] M.J. Atallah and M.T. Goodrich, "Efficient Plane Sweeping in Parallel," Proc. Second Ann. ACM Symp. Computational Geometry, pp. 216225, 1986.
[6] J.L. Bentley and T.A. Ottmann, "Algorithms for Reporting and Counting Geometric Intersections," IEEE Trans. Computers, vol. 28, no. 9, pp. 643647, 1979.
[7] T. Bially, "SpaceFilling Curves: Their Generation and Their Application to Bandwidth Reduction," IEEE Trans. Information Theory, vol. 15, no. 6, pp. 658664, 1969.
[8] G. Brunetti, A. Clematis, B. Falcidieno, A. Sanguineti, and M. Spagnuolo, "Parallel Processing of Spatial Data for Terrain Characterization," Proc. ACM Workshop in GIS, 1994.
[9] H.C. Du and J.S. Sobolewski, "Disk Allocation for Product Files on Multiple Disk Systems," ACM Trans. Database Systems, vol. 7, Mar. 1982.
[10] C. Faloutsos and D. Metaxas, "Disk Allocation Methods Using Error Correcting Codes," IEEE Trans. Computers, Aug. 1991.
[11] M.T. Fang, R.C.T. Lee, and C.C. Chang, "The Idea of Declustering and its Applications," Proc. Int'l Conf. Very Large Databases, 1986.
[12] Z. Fang, P.C. Yew, P. Tang, and C.Q. Zhu, "Dynamic Processor SelfScheduling for General Parallel Nested Loops," Proc. Int'l Conf. Parallel Processing, Aug. 1987.
[13] W.R. Franklin, C. Narayanaswami, M. Kankanahalli, D. Sun, M. Zhou, and P.Y.F. Wu, "Uniform Grids: A Technique for Intersection Detection on Serial and Parallel Machines," Proc. AutoCarto 9, pp. 100109, 1989.
[14] M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NPCompleteness.New York: W.H. Freeman, 1979.
[15] A. Guttman, “RTrees: A Dynamic Index Structure for Spatial Searching,” Proc. ACM SIGMOD Conf. Management of Data, 1984.
[16] W. Hibbard and D. Santek, "Visualizing Large Data Sets in the Earth Sciences," Computer, special issue on visualization in scientific computing, Aug. 1989.
[17] E.G., Hoel and H. Samet, "Data Parallel RTree Algorithms," Proc. Int'l Conf. Parallel Processing, 1993.
[18] E.G., Hoel and H. Samet, "Data Parallel Spatial Join Algorithms," Proc. Int'l Conf. Parallel Processing, 1994.
[19] E.G., Hoel and H. Samet, "Performance of DataParallel Spatial Operations," Proc. 20th VLDB Conf., pp. 156167, 1994.
[20] S.F. Hummel, E. Schonberg, and L.E. Flynn, “Factoring: A Method for Scheduling Parallel Loops,” Comm. ACM, vol. 35, no. 8, pp. 90101, Aug. 1992.
[21] H.V. Jagadish, "Linear Clustering of Objects with Multiple Attributes," Proc. Int'l Conf. Management of Data, pp. 332342, ACM SIGMOD, 1990.
[22] I. Kamel and C. Faloutsos, "Parallel RTrees," Proc. ACM SIGMOD Conf., pp. 195204, 1992.
[23] C.P. Kruskal and A. Weiss, "Allocating Independent Subtasks on Parallel Processors," IEEE Trans. Software Eng., vol. 11, no. 10, pp. 1,0011,016, Oct. 1985.
[24] V. Kumar, A. Grama, A. Gupta, and G. Karypis, Introduction to Parallel Computing: Design and Analysis of Algorithms. Benjamin Cummings, 1994.
[25] V. Kumar, A. Grama, and V.N. Rao, "Scalable Load Balancing Techniques for Parallel Computers," J. Distributed Computing, vol. 7, Mar. 1994.
[26] Y. Liang and B.A. Barsky, "An Analysis and Algorithm for Polygon Clipping," Comm. ACM, vol. 26, Nov. 1983.
[27] D.R. Liu and S. Shekhar, "A Similarity GraphBased Approach to Declustering Problem and its Applications," Proc. 11th Int'l Conf. Data Eng., IEEE CS Press, 1995.
[28] D.R. Pratt, M. Zyda, and K. Kelleher, "Guest Editor's Introduction: Virtual Reality—In the Mind of the Beholder," Computer, special issue on virtual environments, July 1995.
[29] S. Shekhar, S. Ravada, V. Kumar, D. Chubb, and G. Turner, "LoadBalancing in High Performance GIS: Declustering Polygonal Maps," Proc. SSD, Fourth Int'l Symp. Large Spatial Databases, Lecture Notes in Computer Science No. 951, SpringerVerlag, 1995.
[30] R. Sridhar, S.S. Iyengar, and S. Rajanarayanan, "Range Search In Parallel Using Distributed Data Structures," Proc. Int'l Conf. Databases, Parallel Architectures, and Their Applications,Miami Beach, Fla., pp. 1419, 1990.
[31] L. Milor and A. SangiovanniVincentelli, "Optimal Test Set Design for Analog Circuits," Proc. Int'l Conf. ComputerAided Design, IEEE Computer Society Press, Los Alamitos, Calif., 1990, pp. 294297.
[32] F. Wang, "A Parallel Intersection Algorithm for Vector Polygon Overlay," IEEE Computer Graphics&Applications, Mar. 1993.
[33] Y. Zhou, S. Shekhar, and M. Coyle, "Disk Allocation Methods for Parallelizing Grid Files," Proc. 10th Int'l Conf. Data Eng., IEEE CS Press, 1994.