Logarithmic price of buffer downscaling on line metrics
Data Structures and Algorithms
2017-07-25 v3
Abstract
We consider the reordering buffer problem on a line consisting of n equidistant points. We show that, for any constant delta, an (offline) algorithm that has a buffer (1-delta) k performs worse by a factor of Omega(log n) than an offline algorithm with buffer k. In particular, this demonstrates that the O(log n)-competitive online algorithm MovingPartition by Gamzu and Segev (ACM Trans. on Algorithms, 6(1), 2009) is essentially optimal against any offline algorithm with a slightly larger buffer.
Keywords
Cite
@article{arxiv.1610.04915,
title = {Logarithmic price of buffer downscaling on line metrics},
author = {Marcin Bienkowski and Martin Böhm and Łukasz Jeż and Paweł Laskoś-Grabowski and Jan Marcinkowski and Jiří Sgall and Aleksandra Spyra and Pavel Veselý},
journal= {arXiv preprint arXiv:1610.04915},
year = {2017}
}