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Server Scheduling in the Weighted ℓ p Norm

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Book cover LATIN 2004: Theoretical Informatics (LATIN 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2976))

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Abstract

We explain how the apparent goals of the Unix CPU scheduling policy can be formalized using the weighted ℓ p norm of flows. We then show that the online algorithm, Highest Density First (HDF), and the nonclairvoyant algorithm, Weighted Shortest Elapsed Time First (WSETF), are almost fully scalable. That is, they are (1 + ε)-speed O(1)-competitive. Even for unit weights, it was known that there is no O(1)-competitive algorithm. We also give a generic way to transform an algorithm A in an algorithm B in such a way that if A is O(1)-speed O(1)-competitive with respect to some ℓ p norm of flow then B is O(1)-competitive with respect to the ℓ p norm of completion times. Further, if A is online (nonclairvoyant) then B is online (nonclairvoyant). Combining these results gives an O(1)-competitive nonclairvoyant algorithm for ℓ p norms of completion times.

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References

  1. Afrati, F., Bampis, E., Chekuri, C., Karger, D., Kenyon, C., Khanna, S., Milis, I., Queyranne, M., Skutella, M., Stein, C., Sviridenko, M.: Approximation Schemes for Minimizing AverageWeighted Completion Time with Release Dates. In: Foundations of Computer Science (FOCS), pp. 32–44 (1999)

    Google Scholar 

  2. Bansal, N., Dhamdhere, K.: Minimizing Weighted Flow Time. In: ACM/SIAM Symposium on Discrete Algorithms (SODA), pp. 508–516 (2003)

    Google Scholar 

  3. Bansal, N., Pruhs, K.: Server scheduling in the L p norm: a rising tide lifts all boats. In: ACM Symposium on Theory of Computing (STOC), pp. 242–250 (2003)

    Google Scholar 

  4. Becchetti, L., Leonardi, S.: Non-Clairvoyant Scheduling to Minimize the Average Flow Time on Single and Parallel Machines. In: ACM Symposium on Theorey of Computing, STOC (2001)

    Google Scholar 

  5. Becchetti, L., Leonardi, S., Marchetti–Spaccamela, A., Pruhs, K.: Online weighted flow time and deadline scheduling. In: Goemans, M.X., Jansen, K., Rolim, J.D.P., Trevisan, L. (eds.) RANDOM 2001 and APPROX 2001. LNCS, vol. 2129, p. 36. Springer, Heidelberg (2001)

    Chapter  Google Scholar 

  6. Chekuri, C., Khanna, S.: Approximation schemes for preemptive weighted flow time. In: ACM Symposium on Theory of Computing, STOC (2002)

    Google Scholar 

  7. Chekuri, C., Khanna, S., Zhu, A.: Algorithms for weighted flow time. In: ACM Symposium on Theory of Computing, STOC (2001)

    Google Scholar 

  8. Hall, L.A., Schulz, A., Shmoys, D.B., Wein, J.: Scheduling to minimize average completion time: off-line and on-line approximation algorithms. Mathematics of Operations Research 22, 513–549 (1997)

    Article  MATH  MathSciNet  Google Scholar 

  9. Kalyanasundaram, B., Pruhs, K.: Speed is as powerful as clairvoyance. Journal of the ACM 47(4), 617–643 (2000)

    Article  MATH  MathSciNet  Google Scholar 

  10. Kalyanasundaram, B., Pruhs, K.: Minimizing flow time nonclairvoyantly. Journal of the ACM (July 2003)

    Google Scholar 

  11. Karger, D., Stein, C., Wein, J.: Scheduling algorithms. In: CRC Handbook of Theoretical Computer Science (1999)

    Google Scholar 

  12. Knuth, D.: The TeXbook. Addison Wesley, Reading (1986)

    Google Scholar 

  13. Pruhs, K., Sgall, J., Torng, E.: Online Scheduling. To appear in Handbook on Scheduling: Algorithms, Models and Performance Analysis. CRC press, Boca Raton

    Google Scholar 

  14. Motwani, R., Phillips, S., Torng, E.: Non-clairvoyant scheduling. Theoretical Computer Science 130, 17–47 (1994)

    Article  MATH  MathSciNet  Google Scholar 

  15. Tanenbaum, A.: Operating systems: design and implementation. Prentice-Hall, Englewood Cliffs (2001)

    Google Scholar 

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Bansal, N., Pruhs, K. (2004). Server Scheduling in the Weighted ℓ p Norm. In: Farach-Colton, M. (eds) LATIN 2004: Theoretical Informatics. LATIN 2004. Lecture Notes in Computer Science, vol 2976. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-24698-5_47

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  • DOI: https://doi.org/10.1007/978-3-540-24698-5_47

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-21258-4

  • Online ISBN: 978-3-540-24698-5

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