License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.STACS.2014.470
URN: urn:nbn:de:0030-drops-44803
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2014/4480/
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Komm, Dennis ; Královic, Rastislav ; Královic, Richard ; Mömke, Tobias

Randomized Online Algorithms with High Probability Guarantees

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Abstract

We study the relationship between the competitive ratio and the tail distribution of randomized online problems. To this end, we define a broad class of online problems that includes some of the well-studied problems like paging, k-server and metrical task systems on finite metrics, and show that for these problems it is possible to obtain, given an algorithm with constant expected competitive ratio, another algorithm that achieves the same solution quality up to an arbitrarily small constant error with high probability; the "high probability" statement is in terms of the optimal cost. Furthermore, we show that our assumptions are tight in the sense that removing any of them allows for a counterexample to the theorem.

BibTeX - Entry

@InProceedings{komm_et_al:LIPIcs:2014:4480,
  author =	{Dennis Komm and Rastislav Kr{\'a}lovic and Richard Kr{\'a}lovic and Tobias M{\"o}mke},
  title =	{{Randomized Online Algorithms with High Probability Guarantees}},
  booktitle =	{31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014)},
  pages =	{470--481},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-939897-65-1},
  ISSN =	{1868-8969},
  year =	{2014},
  volume =	{25},
  editor =	{Ernst W. Mayr and Natacha Portier},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2014/4480},
  URN =		{urn:nbn:de:0030-drops-44803},
  doi =		{10.4230/LIPIcs.STACS.2014.470},
  annote =	{Keywords: Online Algorithms, Randomization, High Probability}
}

Keywords: Online Algorithms, Randomization, High Probability
Collection: 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014)
Issue Date: 2014
Date of publication: 05.03.2014

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