ABSTRACT
This paper addresses the problem of computing least-cost-path surfaces for massive grid-based terrains. Our approach follows a modular design, enabling the algorithm to make efficient use of memory, disk, and grid computing environments. We have implemented the algorithm in the context of the GRASS open source GIS system and---using our cluster management tool---in a distributed environment. We report experimental results demonstrating that the algorithm is not only of theoretical and conceptual interest but also performs well in practice. Our implementation outperforms standard solutions as dataset size increases relative to available memory and our distributed solver obtains near-linear speedup when preprocessing large terrains for multiple queries.
- A. Aggarwal and J. S. Vitter. The input/output complexity of sorting and related problems. Comm. ACM, 31(9):1116--1127, Sept. 1988. Google ScholarDigital Library
- A. V. Aho, J. E. Hopcroft, and J. D. Ullman. The Design and Analysis of Computer Algorithms. Addison-Wesley, 1974. Google ScholarDigital Library
- L. Arge. External memory data structures. In Handbook of Massive Data Sets. Kluwer, 2002. 313--357. Google ScholarDigital Library
- L. Arge, R. D. Barve, D. Hutchinson, O. Procopiuc, L. Toma, D. E. Vengroff, and R. Wickremesinghe. TPIE user manual and reference, edition 0.9.01a. Duke University, NC, http://www.cs.duke.edu/TPIE/, 1999.Google Scholar
- L. Arge, L. Toma, and J. S. Vitter. I/O-efficient algorithms for problems on grid-based terrains. ACM J. Experimental Algorithmics, 6, 2001. Article 1. Google ScholarDigital Library
- L. Arge, L. Toma, and N. Zeh. I/O-efficient topological sorting of planar DAGs. In Proc. Symp. on Parallel Algorithms and Architectures, pages 85--93, 2003. Google ScholarDigital Library
- C. Breimann and J. Vahrenhold. External memory computational geometry revisited. In U. Meyer, P. Sanders, and J. Sibeyn, editors, Algorithms for Memory Hierarchies, volume 2625 of LNCS, chapter 6, pages 110--148. Springer, 2003.Google Scholar
- Y.-J. Chiang, M. T. Goodrich, E. F. Grove, R. Tamassia, D. E. Vengroff, and J. S. Vitter. External-memory graph algorithms. In Proc. Symp. on Discrete Algorithms, pages 139--149, 1995. Google ScholarDigital Library
- E. W. Dijkstra. A note on two problems in connexion with graphs. Numerische Mathematik, 1:269--271, 1959.Google ScholarDigital Library
- R. W Floyd. Algorithm 97: Shortest path. Comm. ACM, 5(6):345, June 1962. Google ScholarDigital Library
- A. V. Goldberg and C. Harrelson. Computing the shortest path: A* search meets graph theory. In Proc. Symp. on Discrete Algorithms, pages 156--165, 2005. Google ScholarDigital Library
- A. V. Goldberg and R. F. Werneck. An efficient external memory shortest path algorithm. In Proc. Workshop on Algorithm Engineering and Experiments, pages 26--40, 2005.Google Scholar
- R. Gutman. Reach-based routing: A new approach to shortest path algorithms optimized for road networks. In Proc. Workshop on Algorithm Engineering and Experiments, 2004. 100--111.Google Scholar
- E. Köhler, R. H. Möhring, and H. Schilling. Acceleration of shortest path and constrained shortest path computation. In Proc. Workshop on Efficient and Experimental Algorithms, pages 126--138, 2005. Google ScholarDigital Library
- V. Kumar and E. Schwabe. Improved algorithms and data structures for solving graph problems in external memory. In Proc. Symp. on Parallel and Distributed Processing, pages 169--177, 1996. Google ScholarDigital Library
- U. Lauther. An extremely fast, exact algorithm for finding shortest paths in static networks with geographical background. In Geoinformation und Mobilität - von der Forschung zur praktischen Anwendung. Beiträge zu den Münsteraner GI-Tagen, volume 22 of IfGI Prints, pages 219--230, 2004.Google Scholar
- R. H. Möhring, H. Schilling, B. Schütz, D. Wagner, and T. Willhalm. Partitioning graphs to speed up Dijkstra's algorithm. In Proc. Workshop on Efficient and Experimental Algorithms, pages 189--202, 2005. Google ScholarDigital Library
- J. S. Vitter. External memory algorithms and data structures: Dealing with massive data. ACM Comp. Surveys, 33(2):209--271, June 2001. Google ScholarDigital Library
- D. Wagner and T. Willhalm. Drawing graphs to speed up shortest-path computations. In Proc. Workshop on Algorithm Engineering and Experiments, pages 17--25, 2005.Google Scholar
Index Terms
- TerraCost: a versatile and scalable approach to computing least-cost-path surfaces for massive grid-based terrains
Recommendations
Terracost: Computing least-cost-path surfaces for massive grid terrains
This paper addresses the problem of computing least-cost-path surfaces for massive grid terrains. Consider a grid terrain T and let C be a cost grid for T such that every point in C stores a value that represents the cost of traversing the corresponding ...
Phenology of vegetation in Southern England from Envisat MERIS terrestrial chlorophyll index MTCI data
Given the close association between climate change and vegetation response, there is a pressing requirement to monitor the phenology of vegetation and understand further how its metrics vary over space and time. This article explores the use of the ...
Phenology of vegetation in Southern England from Envisat MERIS terrestrial chlorophyll index MTCI data
Given the close association between climate change and vegetation response, there is a pressing requirement to monitor the phenology of vegetation and understand further how its metrics vary over space and time. This article explores the use of the ...
Comments