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.ITCS.2021.67
URN: urn:nbn:de:0030-drops-136065
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2021/13606/
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Emek, Yuval ; Kutten, Shay ; Shi, Yangguang

Online Paging with a Vanishing Regret

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LIPIcs-ITCS-2021-67.pdf (0.6 MB)

Abstract

This paper considers a variant of the online paging problem, where the online algorithm has access to multiple predictors, each producing a sequence of predictions for the page arrival times. The predictors may have occasional prediction errors and it is assumed that at least one of them makes a sublinear number of prediction errors in total. Our main result states that this assumption suffices for the design of a randomized online algorithm whose time-average regret with respect to the optimal offline algorithm tends to zero as the time tends to infinity. This holds (with different regret bounds) for both the full information access model, where in each round, the online algorithm gets the predictions of all predictors, and the bandit access model, where in each round, the online algorithm queries a single predictor.
While online algorithms that exploit inaccurate predictions have been a topic of growing interest in the last few years, to the best of our knowledge, this is the first paper that studies this topic in the context of multiple predictors for an online problem with unbounded request sequences. Moreover, to the best of our knowledge, this is also the first paper that aims for (and achieves) online algorithms with a vanishing regret for a classic online problem under reasonable assumptions.

BibTeX - Entry

@InProceedings{emek_et_al:LIPIcs.ITCS.2021.67,
  author =	{Yuval Emek and Shay Kutten and Yangguang Shi},
  title =	{{Online Paging with a Vanishing Regret}},
  booktitle =	{12th Innovations in Theoretical Computer Science Conference (ITCS 2021)},
  pages =	{67:1--67:20},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-177-1},
  ISSN =	{1868-8969},
  year =	{2021},
  volume =	{185},
  editor =	{James R. Lee},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2021/13606},
  URN =		{urn:nbn:de:0030-drops-136065},
  doi =		{10.4230/LIPIcs.ITCS.2021.67},
  annote =	{Keywords: online paging, inaccurate predictions, multiple predictors, vanishing regret, full information vs. bandit access}
}

Keywords: online paging, inaccurate predictions, multiple predictors, vanishing regret, full information vs. bandit access
Collection: 12th Innovations in Theoretical Computer Science Conference (ITCS 2021)
Issue Date: 2021
Date of publication: 04.02.2021

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