This Article 
 Bibliographic References 
 Add to: 
Declustering and Load-Balancing Methods for Parallelizing Geographic Information Systems
July/August 1998 (vol. 10 no. 4)
pp. 632-655

Abstract—Declustering and load-balancing are important issues in designing a high-performance geographic information system (HPGIS), which is a central component of many interactive applications(such as real-time terrain visualization. The current literature provides efficient methods for declustering spatial point-data. However, there has been little work toward developing efficient declustering methods for collections of extended objects, like chains of line-segments and polygons. In this paper, we focus on the data-partitioning approach to parallelizing GIS operations. We provide a framework for declustering collections of extended spatial objects by identifying the following key issues: 1) the work-load metric, 2) the spatial-extent of the work-load, 3) the distribution of the work-load over the spatial-extent, 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 load-balancing methods on a distributed memory MIMD machine (Cray T3D). Experimental results show that the spatial-extent and the work-load metric are important issues in developing a declustering method. Experiments also show that the replication of data is usually needed to facilitate dynamic load-balancing, 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 load-balancing 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:/
[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. 468-477, 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. 267-288, 1994.
[5] M.J. Atallah and M.T. Goodrich, "Efficient Plane Sweeping in Parallel," Proc. Second Ann. ACM Symp. Computational Geometry, pp. 216-225, 1986.
[6] J.L. Bentley and T.A. Ottmann, "Algorithms for Reporting and Counting Geometric Intersections," IEEE Trans. Computers, vol. 28, no. 9, pp. 643-647, 1979.
[7] T. Bially, "Space-Filling Curves: Their Generation and Their Application to Bandwidth Reduction," IEEE Trans. Information Theory, vol. 15, no. 6, pp. 658-664, 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 Self-Scheduling 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. Auto-Carto 9, pp. 100-109, 1989.
[14] M.R. Garey and D.S. Johnson, Computers and Intractability: A Guide to the Theory of NP-Completeness.New York: W.H. Freeman, 1979.
[15] A. Guttman, “R-Trees: 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 R-Tree 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 Data-Parallel Spatial Operations," Proc. 20th VLDB Conf., pp. 156-167, 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. 90-101, Aug. 1992.
[21] H.V. Jagadish, "Linear Clustering of Objects with Multiple Attributes," Proc. Int'l Conf. Management of Data, pp. 332-342, ACM SIGMOD, 1990.
[22] I. Kamel and C. Faloutsos, "Parallel R-Trees," Proc. ACM SIGMOD Conf., pp. 195-204, 1992.
[23] C.P. Kruskal and A. Weiss, "Allocating Independent Subtasks on Parallel Processors," IEEE Trans. Software Eng., vol. 11, no. 10, pp. 1,001-1,016, 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 Graph-Based 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, "Load-Balancing in High Performance GIS: Declustering Polygonal Maps," Proc. SSD, Fourth Int'l Symp. Large Spatial Databases, Lecture Notes in Computer Science No. 951, Springer-Verlag, 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. 14-19, 1990.
[31] L. Milor and A. Sangiovanni-Vincentelli, "Optimal Test Set Design for Analog Circuits," Proc. Int'l Conf. Computer-Aided Design, IEEE Computer Society Press, Los Alamitos, Calif., 1990, pp. 294-297.
[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.

Index Terms:
Declustering methods, geographic information systems, high performance, load-balancing, polygon clipping, range query.
Shashi Shekhar, Sivakumar Ravada, Vipin Kumar, Douglas Chubb, Greg Turner, "Declustering and Load-Balancing Methods for Parallelizing Geographic Information Systems," IEEE Transactions on Knowledge and Data Engineering, vol. 10, no. 4, pp. 632-655, July-Aug. 1998, doi:10.1109/69.706061
Usage of this product signifies your acceptance of the Terms of Use.