English

Non-Preemptive Flow-Time Minimization via Rejections

Data Structures and Algorithms 2018-05-25 v1

Abstract

We consider the online problem of minimizing weighted flow-time on unrelated machines. Although much is known about this problem in the resource-augmentation setting, these results assume that jobs can be preempted. We give the first constant-competitive algorithm for the non-preemptive setting in the rejection model. In this rejection model, we are allowed to reject an ε\varepsilon-fraction of the total weight of jobs, and compare the resulting flow-time to that of the offline optimum which is required to schedule all jobs. This is arguably the weakest assumption in which such a result is known for weighted flow-time on unrelated machines. While our algorithms are simple, we need a delicate dual-fitting argument to bound the flow-time while only a small fraction of elements are rejected.

Keywords

Cite

@article{arxiv.1805.09602,
  title  = {Non-Preemptive Flow-Time Minimization via Rejections},
  author = {Anupam Gupta and Amit Kumar and Jason Li},
  journal= {arXiv preprint arXiv:1805.09602},
  year   = {2018}
}

Comments

To appear in the ICALP 2018 conference

R2 v1 2026-06-23T02:07:00.474Z