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Streaming Algorithms for Planar Convex Hulls

Authors Martín Farach-Colton, Meng Li, Meng-Tsung Tsai



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Martín Farach-Colton
  • Department of Computer Science, Rutgers University, Piscataway, USA
Meng Li
  • Department of Computer Science, Rutgers University, Piscataway, USA
Meng-Tsung Tsai
  • Department of Computer Science, National Chiao Tung University, Hsinchu, Taiwan

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Martín Farach-Colton, Meng Li, and Meng-Tsung Tsai. Streaming Algorithms for Planar Convex Hulls. In 29th International Symposium on Algorithms and Computation (ISAAC 2018). Leibniz International Proceedings in Informatics (LIPIcs), Volume 123, pp. 47:1-47:13, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2018)
https://doi.org/10.4230/LIPIcs.ISAAC.2018.47

Abstract

Many classical algorithms are known for computing the convex hull of a set of n point in R^2 using O(n) space. For large point sets, whose size exceeds the size of the working space, these algorithms cannot be directly used. The current best streaming algorithm for computing the convex hull is computationally expensive, because it needs to solve a set of linear programs. In this paper, we propose simpler and faster streaming and W-stream algorithms for computing the convex hull. Our streaming algorithm has small pass complexity, which is roughly a square root of the current best bound, and it is simpler in the sense that our algorithm mainly relies on computing the convex hulls of smaller point sets. Our W-stream algorithms, one of which is deterministic and the other of which is randomized, have nearly-optimal tradeoff between the pass complexity and space usage, as we established by a new unconditional lower bound.

Subject Classification

ACM Subject Classification
  • Theory of computation → Computational geometry
Keywords
  • Convex Hulls
  • Streaming Algorithms
  • Lower Bounds

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