Online Non-preemptive Scheduling to Minimize Maximum Weighted Flow-time on Related Machines

Giorgio Lucarelli 1 Benjamin Moseley 2 Kim Thang Nguyen 3 Abhinav Srivastav 3 Denis Trystram 4
1 LCOMS - Laboratoire de Conception, Optimisation et Modélisation des Systèmes
2 Tepper School of Business
3 IBISC - Informatique, Biologie Intégrative et Systèmes Complexes
4 LIG - Laboratoire d'Informatique de Grenoble
Abstract : We consider the problem of scheduling jobs to minimize the maximum weighted flow-time on a set of related machines. When jobs can be preempted this problem is well-understood; for example, there exists a constant competitive algorithm using speed augmentation. When jobs must be scheduled non-preemptively, only hardness results are known. In this paper, we present the first online guarantees for the non-preemptive variant. We present the first constant competitive algorithm for minimizing the maximum weighted flow-time on related machines by relaxing the problem and assuming that the online algorithm can reject a small fraction of the total weight of jobs. This is essentially the best result possible given the strong lower bounds on the non-preemptive problem without rejection.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-02416965
Contributor : Frédéric Davesne <>
Submitted on : Tuesday, December 17, 2019 - 9:59:43 PM
Last modification on : Wednesday, January 8, 2020 - 1:12:14 AM

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  • HAL Id : hal-02416965, version 1

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IBISC | IBISC-AROBAS | UNIV-EVRY | LIG | UNIV-LORRAINE | LCOMS-UL | CNRS | UNIV-PARIS-SACLAY | UGA

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Giorgio Lucarelli, Benjamin Moseley, Kim Thang Nguyen, Abhinav Srivastav, Denis Trystram. Online Non-preemptive Scheduling to Minimize Maximum Weighted Flow-time on Related Machines. 39th IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2019), Dec 2019, Bombay, India. ⟨hal-02416965⟩

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