Skip to main content

On Weighted Balls-into-Bins Games

  • Conference paper
Book cover STACS 2005 (STACS 2005)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 3404))

Included in the following conference series:

Abstract

We consider the well-known problem of randomly allocating m balls into n bins. We investigate various properties of single-choice games as well as multiple-choice games in the context of weighted balls. We are particularly interested in questions that are concerned with the distribution of ball weights, and the order in which balls are allocated. Do any of these parameters influence the maximum expected load of any bin, and if yes, then how?

The problem of weighted balls is of practical relevance. Balls-into-bins games are frequently used to conveniently model load balancing problems. Here, weights can be used to model resource requirements of the jobs, i.e., memory or running time.

A full version of this paper including all proofs can be found at http://www.dur.ac.uk/tom.friedetzky/pub/

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Azar, Y., Broder, A.Z., Karlin, A.R., Upfal, E.: Balanced Allocations. SIAM J. Computing 29, 180–200 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  2. Berenbrink, P., Czumaj, A., Steger, A., Vöcking, B.: Balanced Allocations: The Heavily Loaded Case. In: Proc. of the 30th Annual ACM Symposium on Theory of Computing (STOC 2000), pp. 745–754 (2000)

    Google Scholar 

  3. Bubley, R., Dyer, M.E.: Path Coupling: A Technique for Proving Rapid Mixing in Markov Chains. In: Proc. of the 38th Annual Symposium on Foundations of Computer Science (FOCS 1997), pp. 223–231 (1997)

    Google Scholar 

  4. Berenbrink, P.: Randomized Allocation of Independent Tasks. University of Paderborn (2000)

    Google Scholar 

  5. Berenbrink, P., auf der Heide, F.M., Schröder, K.: Allocating Weighted Jobs in Parallel. Theory of Computing Systems 32, 281–300 (1999)

    Article  MATH  MathSciNet  Google Scholar 

  6. Chang, C.-S.: A New Ordering for Stochastic Majorization: Theory and Applications. Advances in Applied Probability 24, 604–634 (1992)

    Article  MATH  MathSciNet  Google Scholar 

  7. Czumaj, A.: Recovery Time of Dynamic Allocation Processes. Theory of Computing Systems 33, 465–487 (2000)

    Article  MATH  Google Scholar 

  8. Czumaj, A., Stemann, V.: Randomized Allocation Processes. Random Structures and Algorithms 18, 297–331 (2001)

    Article  MATH  MathSciNet  Google Scholar 

  9. Czumaj, A., Rily, C., Scheideler, C.: Perfectly Balanced Allocation. In: Arora, S., Jansen, K., Rolim, J.D.P., Sahai, A. (eds.) RANDOM 2003 and APPROX 2003. LNCS, vol. 2764, pp. 240–251. Springer, Heidelberg (2003)

    Google Scholar 

  10. Karp, R.M., Luby, M., auf der Heide, F.M.: Efficient PRAM Simulation on a Distributed Memory Machine. In: Proc. of the 22nd Annual ACM Symposium on Theory of Computing (STOC 1992), pp. 318–326 (1992)

    Google Scholar 

  11. Koutsoupias, E., Mavronicolas, M., Spirakis, P.G.: Approximate Equilibria and Ball Fusion. Theory of Computing Systems 36, 683–693 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  12. Marshall, A.W., Olkin, I.: Inequalities: Theory of Majorization and Its Applications. Academic Press, London (1979)

    MATH  Google Scholar 

  13. Mitzenmacher, M., Richa, A.W., Sitaraman, R.: The Power of Two Random Choices: A Survey of Techniques and Results. In: Handbook of Randomized Computing (2000)

    Google Scholar 

  14. Mitzenmacher, M., Prabhakar, B., Shah, D.: Load Balancing with Memory. In: Proc. of the 43rd Annual IEEE Symposium on Foundations of Computer Science (FOCS 2002), pp. 799–808 (2002)

    Google Scholar 

  15. Motwani, R., Raghavan, P.: Randomized Algorithms. Cambridge University Press, Cambridge (1995)

    MATH  Google Scholar 

  16. Sinclair, A.: Algorithms for Random Generation and Counting: A Markov Chain Approach. Birkhäuser, Boston (1993)

    MATH  Google Scholar 

  17. Stemann, V.: Parallel Balanced Allocations. In: Proc. of the 8th ACM Symposium on Parallel Algorithms and Architectures (SPAA 1996), pp. 261–269 (1996)

    Google Scholar 

  18. Sanders, P., Egner, S., Korst, J.H.M.: Fast Concurrent Access to Parallel Disks. Algorithmica 35, 21–55 (2003)

    Article  MATH  MathSciNet  Google Scholar 

  19. Vöcking, B.: How Asymmetry Helps Load Balancing. In: Proc. of the 40th Annual IEEE Symposium on Foundations of Computer Science (FOCS 1999), pp. 131–140 (1999)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2005 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Berenbrink, P., Friedetzky, T., Hu, Z., Martin, R. (2005). On Weighted Balls-into-Bins Games. In: Diekert, V., Durand, B. (eds) STACS 2005. STACS 2005. Lecture Notes in Computer Science, vol 3404. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-31856-9_19

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-31856-9_19

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-24998-6

  • Online ISBN: 978-3-540-31856-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics