Advertisement

OnlineMin: A Fast Strongly Competitive Randomized Paging Algorithm

  • Gerth Stølting Brodal
  • Gabriel Moruz
  • Andrei Negoescu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7164)

Abstract

In the field of online algorithms paging is one of the most studied problems. For randomized paging algorithms a tight bound of H k on the competitive ratio has been known for decades, yet existing algorithms matching this bound have high running times. We present the first randomized paging approach that both has optimal competitiveness and selects victim pages in subquadratic time. In fact, if k pages fit in internal memory the best previous solution required O(k 2) time per request and O(k) space, whereas our approach takes also O(k) space, but only O(logk) time in the worst case per page request.

Keywords

Competitive Ratio Online Algorithm Page Request Cache Content Future Request 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. 1.
    Achlioptas, D., Chrobak, M., Noga, J.: Competitive analysis of randomized paging algorithms. Theoretical Computer Science 234(1-2), 203–218 (2000)MathSciNetzbMATHCrossRefGoogle Scholar
  2. 2.
    Albers, S.: Online algorithms: a survey. Mathematical Programming 97(1–2), 3–26 (2003)MathSciNetzbMATHGoogle Scholar
  3. 3.
    Bein, W.W., Larmore, L.L., Noga, J., Reischuk, R.: Knowledge state algorithms. Algorithmica 60(3), 653–678 (2011)MathSciNetzbMATHCrossRefGoogle Scholar
  4. 4.
    Belady, L.A.: A study of replacement algorithms for virtual-storage computer. IBM Systems Journal 5(2), 78–101 (1966)CrossRefGoogle Scholar
  5. 5.
    Borodin, A., El-Yaniv, R.: Online computation and competitive anlysis. Cambridge University Press (1998)Google Scholar
  6. 6.
    Chrobak, M., Koutsoupias, E., Noga, J.: More on randomized on-line algorithms for caching. Theoretical Computer Science 290(3), 1997–2008 (2003)MathSciNetzbMATHCrossRefGoogle Scholar
  7. 7.
    Fiat, A., Karp, R.M., Luby, M., McGeoch, L.A., Sleator, D.D., Young, N.E.: Competitive paging algorithms. Journal of Algorithms 12(4), 685–699 (1991)zbMATHCrossRefGoogle Scholar
  8. 8.
    Fiat, A., Woeginger, G.J. (eds.): Online Algorithms, The State of the Art (the book grow out of a Dagstuhl Seminar (June 1996, 1998)Google Scholar
  9. 9.
    Karlin, A.R., Manasse, M.S., Rudolph, L., Sleator, D.D.: Competitive snoopy caching. Algorithmica 3, 77–119 (1988)MathSciNetCrossRefGoogle Scholar
  10. 10.
    Koutsoupias, E., Papadimitriou, C.H.: Beyond competitive analysis. In: Proc. 35th Symposium on Foundations of Computer Science, pp. 394–400 (1994)Google Scholar
  11. 11.
    McGeoch, L.A., Sleator, D.D.: A strongly competitive randomized paging algorithm. Algorithmica 6(6), 816–825 (1991)MathSciNetzbMATHCrossRefGoogle Scholar
  12. 12.
    Sleator, D.D., Tarjan, R.E.: Amortized efficiency of list update and paging rules. Communications of the ACM 28(2), 202–208 (1985)MathSciNetCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Gerth Stølting Brodal
    • 1
  • Gabriel Moruz
    • 2
  • Andrei Negoescu
    • 2
  1. 1.MADALGO, Department of Computer ScienceAarhus UniversityAarhus NDenmark
  2. 2.Goethe University Frankfurt am MainFrankfurt am MainGermany

Personalised recommendations