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Space-Constrained Interval Selection

  • Yuval Emek
  • Magnús M. Halldórsson
  • Adi Rosén
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7391)

Abstract

We study streaming algorithms for the interval selection problem: finding a maximum cardinality subset of disjoint intervals on the line. A deterministic 2-approximation streaming algorithm for this problem is developed, together with an algorithm for the special case of proper intervals, achieving improved approximation ratio of 3/2. We complement these upper bounds by proving that they are essentially best possible in the streaming setting: it is shown that an approximation ratio of 2 − ε (or 3 / 2 − ε for proper intervals) cannot be achieved unless the space is linear in the input size. In passing, we also answer an open question of Adler and Azar [1] regarding the space complexity of constant-competitive randomized preemptive online algorithms for the same problem.

Keywords

Competitive Ratio Online Algorithm Online Schedule Actual Interval Memory Image 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Yuval Emek
    • 1
  • Magnús M. Halldórsson
    • 2
  • Adi Rosén
    • 3
  1. 1.ETH ZurichZurichSwitzerland
  2. 2.ICE-TCS, School of Computer ScienceReykjavik UniversityIceland
  3. 3.CNRS and Université Paris DiderotFrance

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