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Terracost: Computing least-cost-path surfaces for massive grid terrains

Published: 12 June 2008 Publication History

Abstract

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 point in T. Given C and a set of sources ST, a least-cost-path grid Δ for T is a grid such that every point in Δ represents the distance to the source in S that can be reached with minimal cost. We present a scalable approach to computing least-cost-path grids. Our algorithm, terracost, is derived from our previous work on I/O-efficient shortest paths on grids and uses O(sort(n)) I/Os, where sort(n) is the complexity of sorting n items of data in the I/O-model of Aggarwal and Vitter. We present the design, the analysis, and an experimental study of terracost. An added benefit of the algorithm underlying terracost is that it naturally lends itself to parallelization. We have implemented terracost in a distributed environment using our cluster management tool and report on experiments that show that it obtains speedup near-linear with the size of the cluster. To the best of our knowledge, this is the first experimental evaluation of a multiple-source least-cost-path algorithm in the external memory setting.

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Published In

cover image ACM Journal of Experimental Algorithmics
ACM Journal of Experimental Algorithmics  Volume 12, Issue
2008
507 pages
ISSN:1084-6654
EISSN:1084-6654
DOI:10.1145/1227161
Issue’s Table of Contents
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 12 June 2008
Accepted: 01 October 2007
Revised: 01 August 2007
Received: 01 December 2006
Published in JEA Volume 12

Author Tags

  1. Data structures and algorithms
  2. Dijkstra's algorithm
  3. I/O-efficiency
  4. shortest paths
  5. terrain data

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  • (2016)Least-Cost Modelling and Landscape Ecology: Concepts, Applications, and OpportunitiesCurrent Landscape Ecology Reports10.1007/s40823-016-0006-91:1(40-53)Online publication date: 2-Jun-2016
  • (2013)A Smoothest Path algorithm and its visualization tool2013 Proceedings of IEEE Southeastcon10.1109/SECON.2013.6567453(1-6)Online publication date: Apr-2013
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