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Select and Permute: An Improved Online Framework for Scheduling to Minimize Weighted Completion Time

  • Samir Khuller
  • Jingling Li
  • Pascal Sturmfels
  • Kevin Sun
  • Prayaag Venkat
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10807)

Abstract

In this paper, we introduce a new online scheduling framework for minimizing total weighted completion time in a general setting. The framework is inspired by the work of Hall et al. [10] and Garg et al. [8], who show how to convert an offline approximation to an online scheme. Our framework uses two offline approximation algorithms—one for the simpler problem of scheduling without release times, and another for the minimum unscheduled weight problem—to create an online algorithm with provably good competitive ratios.

We illustrate multiple applications of this method that yield improved competitive ratios. Our framework gives algorithms with the best or only-known competitive ratios for the concurrent open shop, coflow, and concurrent cluster models. We also introduce a randomized variant of our framework based on the ideas of Chakrabarti et al. [3] and use it to achieve improved competitive ratios for these same problems.

Keywords

Coflow scheduling Concurrent clusters Concurrent open shop Online algorithms 

Notes

Acknowledgements

We would like to thank Sungjin Im and Clifford Stein for directing us to [3, 17], and William Gasarch for organizing the REU program.

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Samir Khuller
    • 1
  • Jingling Li
    • 1
  • Pascal Sturmfels
    • 2
  • Kevin Sun
    • 3
  • Prayaag Venkat
    • 1
  1. 1.University of MarylandCollege ParkUSA
  2. 2.University of MichiganAnn ArborUSA
  3. 3.Duke UniversityDurhamUSA

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