Paging more than one page

  • Esteban Feuerstein
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 911)


In this paper we extend the Paging Problem to the case in which each request specifies not a single page but a set of pages that must be present in fast memory to serve the request. The interest on this extension is motivated by many applications in which each task that must be performed by the system may require the presence of more than one page in fast memory to be executed. The cardinalities of the sets involved in each query are not fixed, and hence the advantage that could be obtained considering requests of cardinality greater than one as a lookahead ([4]) can not be considered as granted. We introduce three different cost models that can be applied in this framework, namely the Full, Partial and 0/1-cost models. The efficiency of our algorithms will be measured using competitive analysis techniques.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    A. Aggarwal, B. Alpern, A.K. Chandra and M. Snir, A model for hierarchical memory, Proc. 19th Annual ACM Symposium on Theory of Computing 305–314 (1987).Google Scholar
  2. 2.
    A. Aggarwal and A.K. Chandra, Virtual memory algorithms, Proc. 20th Annual ACM Symposium on Theory of Computing 173–185 (1988).Google Scholar
  3. 3.
    A. Aggarwal, A.K. Chandra and M. Snir, Hierarchical memory with block transfer, Proc. 28th. Annual Symposium on Foundations of Computer Science 204–216 (1987).Google Scholar
  4. 4.
    S. Albers, The influence of lookahead in competitive paging algorithms, Proc. First Annual European Symposium on Algorithms, Springer-Verlag LNCS, 1–12 (1993).Google Scholar
  5. 5.
    L. A. Belady, A study of replacement algorithms for virtual storage computers, IBM Syst. J. 5 78–101 (1966).Google Scholar
  6. 6.
    A. Borodin, Sandy Irani, P. Raghavan and B. Schieber, Competitive paging with locality of reference, Proc. 23rd Annual ACM Symposium on Theory of Computing 249–259 (1991).Google Scholar
  7. 7.
    A. Borodin, N. Linial, and M. Saks, An optimal online algorithm for metrical task systems, Proc. 19th Annual ACM Symposium on Theory of Computing 373–382 (1987).Google Scholar
  8. 8.
    E. Feuerstein, A. Marchetti-Spaccamela, Memory paging for connectivity and path problems in graphs, Proc. 4th Annual Symposium on Algorithms and Computation, Springer-Verlag LNCS 762 416–425 (1993)Google Scholar
  9. 9.
    A. Fiat, R.M. Karp, M. Luby, L.A. McGeoch, D.D. Sleator and N.E. Young, Competitive paging algorithms, Journal of Algorithms 12 685–699 (1991).CrossRefGoogle Scholar
  10. 10.
    A. Karlin, M. Manasse, L. Rudolph and D. Sleator, Competitive snoopy caching, Algorithmica 3 79–119, (1988).MathSciNetGoogle Scholar
  11. 11.
    M.S. Manasse, L.A. McGeoch and D. Sleator, Competitive algorithms for server problems, Journal of Algorithms 11 208–230 (1990).CrossRefGoogle Scholar
  12. 12.
    L. A. McGeoch and D. Sleator, A strongly competitive randomized paging algorithm, Technical Report CMU-CS-89-122 (1989).Google Scholar
  13. 13.
    Mark Nodine, Michael Goodrich, Jeffrey Scott Vitter, Blocking for external Graph Searching, Technical Report CS-92-44 (1992).Google Scholar
  14. 14.
    P. Raghavan and M. Snir, Memory versus randomization in on-line algorithms, IBM Research Report RC 15622 (1990).Google Scholar
  15. 15.
    D. Sleator and R.E. Tarjan, Amortized efficiency of list update and paging algorithms, Comm. ACM 28 202–208 (1985).CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 1995

Authors and Affiliations

  • Esteban Feuerstein
    • 1
  1. 1.Dipartimento di Informatica e SistemisticaUniversità di Roma “La Sapienza”RomaItalia

Personalised recommendations