Weighted k-server bounds via combinatorial dichotomies

N. Bansal, M. Elias, G. Koumoutsos

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

4 Citations (Scopus)

Abstract

The weighted k-server problem is a natural generalization of the k-server problem where each server has a different weight. We consider the problem on uniform metrics, which corresponds to a natural generalization of paging. Our main result is a doubly exponential lower bound on the competitive ratio of any deterministic online algorithm, that essentially matches the known upper bounds for the problem and closes a large and long-standing gap. The lower bound is based on relating the weighted k-server problem to a certain combinatorial problem and proving a Ramsey-theoretic lower bound for it. This combinatorial connection also reveals several structural properties of low cost feasible solutions to serve a sequence of requests. We use this to show that the generalized Work Function Algorithm achieves an almost optimum competitive ratio, and to obtain new refined upper bounds on the competitive ratio for the case of d different weight classes.
Original languageEnglish
Title of host publication2017 IEEE 58th Annual Symposium on Foundations of Computer Science (FOCS), 15-17 October 2017, Berkeley, California
Place of PublicationPiscataway
PublisherInstitute of Electrical and Electronics Engineers
Pages493-504
Number of pages12
ISBN (Electronic)978-1-5386-3464-6
ISBN (Print)978-1-5386-3465-3
DOIs
Publication statusPublished - 2017
Event58th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2017), October 15-17, 2017, Berkeley, California - DoubleTree Hotel at the Berkeley Marina, Berkeley, United States
Duration: 15 Oct 201717 Oct 2017
https://focs17.simons.berkeley.edu/

Conference

Conference58th Annual IEEE Symposium on Foundations of Computer Science (FOCS 2017), October 15-17, 2017, Berkeley, California
Abbreviated titleFOCS 2017
CountryUnited States
CityBerkeley
Period15/10/1717/10/17
Internet address

Keywords

  • competitive analysis
  • online algorithms
  • weighted k-server

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