Elsevier

Journal of Algorithms

Volume 11, Issue 2, June 1990, Pages 208-230
Journal of Algorithms

Competitive algorithms for server problems

https://doi.org/10.1016/0196-6774(90)90003-WGet rights and content

Abstract

The k-server problem is that of planning the motion of k mobile servers on the vertices of a graph under a sequence of requests for service. Each request consists of the name of a vertex, and is satisfied by placing a server at the requested vertex. The requests must be satisfied in their order of occurrence. The cost of satisfying a sequence of requests is the distance moved by the servers. In this paper we study on-line algorithms for this problem from the competitive point of view. That is, we seek to develop on-line algorithms whose performance on any sequence of requests is as close as possible to the performance of the optimum off-line algorithm. We obtain optimally competitive algorithms for several important cases. Because of the flexibility in choosing the distances in the graph and the number of servers, the k-server problem can be used to model a number of important paging and caching problems. It can also be used as a building block for solving more general problems. We show how server algorithms can be used to solve a seemingly more general class of problems known as task systems.

References (11)

  • D. Black and D. D. Sleator, Algorithms for the 1-server problem with excursions, in...
  • A Borodin et al.

    An optimal online algorithm for metrical task systems

  • A.R Calderbank et al.

    Sequencing problems in two-server systems

    Math. Oper. Res.

    (1985)
  • A.R Calderbank et al.

    Sequencing two servers on a sphere

    Commun. Statist.-Stochastic Models

    (1985)
  • A Fiat et al.

    Competitive Paging Algorithms

    Carnegie Mellon University Computer Science technical report CMU-CS-88–196

    (1988)
There are more references available in the full text version of this article.

Cited by (385)

View all citing articles on Scopus

Part of the work of the second author was done at Carnegie-Mellon University and was supported by an NSF Graduate Fellowship and by NSF Grants DCR-8352081 and MCS-8308805.

Partial support provided by DARPA, ARPA order 4976, Amendment 20, monitored by the Air Force Avionics Laboratory under Contract F33615-87-C-1499, and by the National Science Foundation under Grant CCR-8658139.

View full text