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Algorithms minimizing mean flow time: schedule-length properties

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Summary

The mean flow time of a schedule provides a measure of the average time that a task spends within a computer system, and also the average number of unfinished tasks in the system. The mean flow time of a schedule is defined to be the sum of the finishing times of all tasks in the system. On a system of identical processors O(nlog n) algorithms exist for determining minimal mean flow time schedules for n independent tasks. In general, there will be a large class C of schedules, of widely differing lengths, that all minimize mean flow time. The problem of finding the shortest schedule in C is NP-complete. We give heuristics that find schedules in C that are no more than 25% longer than the shortest schedule in C. The advantage of a short schedule is that processor utilization is high.

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References

  1. Bruno, J. L., Coffman, E. G. Jr., Sethi, R.: Scheduling independent tasks to reduce mean finishing time. Comm. ACM 17, 382–387 (1974)

    Article  MathSciNet  Google Scholar 

  2. Bruno, J. L., Coffman, E. G. Jr., Sethi, R.: Algorithms for minimizing mean flow time. Information Processing 74. Amsterdam: 1974 p. 504–510 North-Holland

    Google Scholar 

  3. Conway, R. W., Maxwell, W. L., Miller, L. W.: Theory of scheduling. Reading (Mass.): Addison Wesley, 1967

    MATH  Google Scholar 

  4. Garey, M. R., Johnson, D. S.: Complexity results for multiprocessor scheduling under resource constraints. SIAM J. Computing 4, 399–411 (1975)

    MathSciNet  MATH  Google Scholar 

  5. Graham, R. L.: Bounds on multiprocessing anomalies and related packing algorithms. Proc. AFIPS SJCC 40 Montvale (N.J.): AFIPS-Press 1972 p. 205–217

    Google Scholar 

  6. Horowitz, E., Sahni, S.: Exact and approximate algorithms for scheduling nonidentical processors. Tech. Rep. 74-22, University of Minnesota, Minneapolis, Minn. Sep 74 (to appear, JACM)

  7. Karp, R. M.: Reducibility among combinatorial problems. In: R. E. Miller and J. W. Thatcher (ed.): Complexity of computer computations. New York, N.Y.: Plenum Press 1972 p. 85–101

    Chapter  Google Scholar 

  8. Ullman, J. D.: NP-complete scheduling problems. J. Computer and System Sciences 10, 3 384–393 (1975)

    Article  MathSciNet  Google Scholar 

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Authors and Affiliations

  1. Computer Science Dept., The Pennsylvania State Univ., 16802, Pennsylvania, USA

    E. G. Coffman Jr. & Ravi Sethi

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  1. E. G. Coffman Jr.
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  2. Ravi Sethi
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Additional information

Partial support provided by NSF Grant GJ-28290

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Coffman, E.G., Sethi, R. Algorithms minimizing mean flow time: schedule-length properties. Acta Informatica 6, 1–14 (1976). https://doi.org/10.1007/BF00263740

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  • DOI: https://doi.org/10.1007/BF00263740

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