Comparison-based time-space lower bounds for selection

  • Authors:
  • Timothy M. Chan

  • Affiliations:
  • University of Waterloo, Ontario, Canada

  • Venue:
  • ACM Transactions on Algorithms (TALG)
  • Year:
  • 2010

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Abstract

We establish the first nontrivial lower bounds on time-space trade-offs for the selection problem. We prove that any comparison-based randomized algorithm for finding the median requires Ω(nlog logS n) expected time in the RAM model (or more generally in the comparison branching program model), if we have S bits of extra space besides the read-only input array. This bound is tight for all S ≫ log n, and remains true even if the array is given in a random order. Our result thus answers a 16-year-old question of Munro and Raman [1996], and also complements recent lower bounds that are restricted to sequential access, as in the multipass streaming model [Chakrabarti et al. 2008b]. We also prove that any comparison-based, deterministic, multipass streaming algorithm for finding the median requires Ω(nlog*(n/s)+ nlogs n) worst-case time (in scanning plus comparisons), if we have s cells of space. This bound is also tight for all s ≫log2 n. We get deterministic lower bounds for I/O-efficient algorithms as well. The proofs in this article are self-contained and do not rely on communication complexity techniques.