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On the Variance of the Least Attained Service Policy and Its Use in Multiple Bottleneck Networks

  • Matthias Auchmann
  • Guillaume Urvoy-Keller
Conference paper
  • 382 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5425)

Abstract

Size-based scheduling has proved to be effective in a lot of scenarios involving Internet traffic. In this work, we focus on the Least Attained Service Policy, a popular size-based scheduling policy. We tackle two issues that have not received much attention so far. Firstly, the variance of the conditional response time. We prove that the classification proposed by Wierman et al. [11], which classifies LAS as an always unpredictable policy, is overly pessimistic. We illustrate the latter by focusing on the M/M/1/LAS queue. Secondly, we consider LAS queues in tandem. We provide preliminary results concerning the characterization of the output process of an M/M/1/LAS queue and the conditional average response time of LAS queues in tandem.

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References

  1. 1.
    Auchmann, M., Urvoy-Keller, G.: On the variance of the least attained service policy and its use in multiple bottleneck networks. Technical Report RR-08-224, Institut Eurecom, France (June 2008), http://www.eurecom.fr/util/popuppubli.fr.htm?page=copyright&id=2497
  2. 2.
    Brown, P.: Comparing fb and ps scheduling policies. Technical report, Orange Labs (2008)Google Scholar
  3. 3.
    Crovella, M.E., et al.: A Practical Guide to Heavy Tails, ch. 3. Chapman and Hall, New-York (1998)Google Scholar
  4. 4.
    Harchol-Balter, M., Schroeder, B., Bansal, N., Agrawal, M.: Size-based scheduling to improve web performance. ACM Trans. Comput. Syst. 21(2), 207–233 (2003)CrossRefGoogle Scholar
  5. 5.
    Hernandez-Campos, F., Karaliopoulos, M., Papadopouli, M., Shen, H.: Spatio-temporal modeling of traffic workload in a campus wlan. In: WICON 2006, p. 1 (2006)Google Scholar
  6. 6.
    Hu, M., Zhang, J., Sadowsky, J.: Size-aided opportunistic scheduling in wireless networks. In: GLOBECOM 2003. IEEE, Los Alamitos (2003)Google Scholar
  7. 7.
    Nuyens, M., Wierman, A.: The foreground-background queue: A survey. Perform. Eval. 65(3-4), 286–307 (2008)CrossRefGoogle Scholar
  8. 8.
    Rai, I.A., Urvoy-Keller, G., Biersack, E.W.: Analysis of las scheduling for job size distributions with high variance. In: Proc. ACM SIGMETRICS, June 2003, pp. 218–228 (2003)Google Scholar
  9. 9.
    Rai, I.A., Urvoy-Keller, G., Vernon, M., Biersack, E.W.: Performance models for las-based scheduling disciplines in a packet switched network. In: ACM SIGMETRICS-Performance (June 2004)Google Scholar
  10. 10.
    Schrage, L.E.: The queue m/g/1 with feedback to lower priority queues. Management Science 13(7), 466–474 (1967)CrossRefGoogle Scholar
  11. 11.
    Wierman, A., Harchol-Balter, M.: Classifying scheduling policies with respect to higher moments of conditional response time. ACM SIGMETRICS Performance Evaluation Review 33(1), 229–240 (2005)CrossRefGoogle Scholar
  12. 12.
    Yashkov, S.: Processor-sharing queues: some progress in analysis. Queueing Systems: Theory and Applications 2(1), 1–17 (1987)MathSciNetCrossRefzbMATHGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2009

Authors and Affiliations

  • Matthias Auchmann
    • 1
  • Guillaume Urvoy-Keller
    • 2
  1. 1.Technische Universität WienAustria
  2. 2.EurecomFrance

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