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  • 标题:Online Non-Preemptive Scheduling to Minimize Maximum Weighted Flow-Time on Related Machines
  • 本地全文:下载
  • 作者:Giorgio Lucarelli ; Benjamin Moseley ; Nguyen Kim Thang
  • 期刊名称:LIPIcs : Leibniz International Proceedings in Informatics
  • 电子版ISSN:1868-8969
  • 出版年度:2019
  • 卷号:150
  • 页码:1-12
  • DOI:10.4230/LIPIcs.FSTTCS.2019.24
  • 出版社:Schloss Dagstuhl -- Leibniz-Zentrum fuer Informatik
  • 摘要: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.
  • 关键词:Online Algorithms; Scheduling; Resource Augmentation
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