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Online Preemptive Scheduling on Parallel Machines

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Encyclopedia of Algorithms

Years and Authors of Summarized Original Work

  • 2009; Ebenlendr, Jawor, Sgall

  • 2010; Ebenlendr

  • 2011; Ebenlendr, Sgall

Problem Definition

We consider an online version of the classical problem of preemptive scheduling on uniformly related machines.

We are given m machines with speeds s1s2s m and a sequence of jobs, each described by its processing time (length). The actual time needed to process a job with length p on a machine with speed s is ps. In the preemptive version, each job may be divided into several pieces, which can be assigned to different machines in disjoint time slots. (A job may be scheduled in several time slots on the same machine, and there may be times when a partially processed job is not running at all.) The objective is to find a schedule of all jobs in which the maximal completion time (makespan) is minimized.

In the online problem, jobs arrive one by one and the algorithm needs to assign each incoming job to some time slots on some machines, without...

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Recommended Reading

  1. Berman P, Charikar M, Karpinski M (2000) On-line load balancing for related machines. J. Algorithms 35:108–121

    Article  MathSciNet  MATH  Google Scholar 

  2. Ebenlendr T (2010) Semi-online preemptive scheduling: study of special cases. In: Proceedings of 8th international conference on parallel processing and applied mathematics (PPAM 2009), part II, Wroclaw. Lecture notes in computer science, vol 6068. Springer, pp 11–20

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  3. Ebenlendr T (2011) Combinatorial algorithms for online problems: semi-online scheduling on related machines. Ph.D. thesis, Charles University, Prague

    Google Scholar 

  4. Ebenlendr T, Jawor W, Sgall J (2009) Preemptive online scheduling: optimal algorithms for all speeds. Algorithmica 53:504–522

    Article  MathSciNet  MATH  Google Scholar 

  5. Ebenlendr T, Sgall J (2004) Optimal and online preemptive scheduling on uniformly related machines. In: Proceedings of 21st symposium on theoretical aspects of computer science (STACS), Montpellier. Lecture notes in computer science, vol 2996. Springer, pp 199–210

    Google Scholar 

  6. Ebenlendr T, Sgall J (2011) Semi-online preemptive scheduling: one algorithm for all variants. Theory Comput Syst 48:577–613

    Article  MathSciNet  MATH  Google Scholar 

  7. Epstein L, Sgall J (2000) A lower bound for on-line scheduling on uniformly related machines. Oper Res Lett 26:17–22

    Article  MathSciNet  MATH  Google Scholar 

  8. Graham RL (1966) Bounds for certain multiprocessing anomalies. Bell Syst Tech J 45: 1563–1581

    Article  MATH  Google Scholar 

  9. Graham RL (1969) Bounds on multiprocessing timing anomalies. SIAM J Appl Math 17: 263–269

    MathSciNet  MATH  Google Scholar 

  10. Seiden S, Sgall J, Woeginger GJ (2000) Semi-online scheduling with decreasing job sizes. Oper Res Lett 27:215–221

    Article  MathSciNet  MATH  Google Scholar 

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Correspondence to Jiřı́ Sgall .

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Sgall, J. (2016). Online Preemptive Scheduling on Parallel Machines. In: Kao, MY. (eds) Encyclopedia of Algorithms. Springer, New York, NY. https://doi.org/10.1007/978-1-4939-2864-4_501

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