License: Creative Commons Attribution 3.0 Unported license (CC-BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.APPROX-RANDOM.2018.16
URN: urn:nbn:de:0030-drops-94205
URL: https://drops.dagstuhl.de/opus/volltexte/2018/9420/
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Kulkarni, Janardhan ; Li, Shi

Flow-time Optimization for Concurrent Open-Shop and Precedence Constrained Scheduling Models

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LIPIcs-APPROX-RANDOM-2018-16.pdf (0.5 MB)


Abstract

Scheduling a set of jobs over a collection of machines is a fundamental problem that needs to be solved millions of times a day in various computing platforms: in operating systems, in large data clusters, and in data centers. Along with makespan, flow-time, which measures the length of time a job spends in a system before it completes, is arguably the most important metric to measure the performance of a scheduling algorithm. In recent years, there has been a remarkable progress in understanding flow-time based objective functions in diverse settings such as unrelated machines scheduling, broadcast scheduling, multi-dimensional scheduling, to name a few. Yet, our understanding of the flow-time objective is limited mostly to the scenarios where jobs have no dependencies. On the other hand, in almost all real world applications, think of MapReduce settings for example, jobs have dependencies that need to be respected while making scheduling decisions. In this paper, we take first steps towards understanding this complex problem. In particular, we consider two classical scheduling problems that capture dependencies across jobs: 1) concurrent open-shop scheduling (COSSP) and 2) precedence constrained scheduling. Our main motivation to study these problems specifically comes from their relevance to two scheduling problems that have gained importance in the context of data centers: co-flow scheduling and DAG scheduling. We design almost optimal approximation algorithms for COSSP and PCSP, and show hardness results.

BibTeX - Entry

@InProceedings{kulkarni_et_al:LIPIcs:2018:9420,
  author =	{Janardhan Kulkarni and Shi Li},
  title =	{{Flow-time Optimization for Concurrent Open-Shop and Precedence Constrained Scheduling Models}},
  booktitle =	{Approximation, Randomization, and Combinatorial  Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)},
  pages =	{16:1--16:21},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-085-9},
  ISSN =	{1868-8969},
  year =	{2018},
  volume =	{116},
  editor =	{Eric Blais and Klaus Jansen and Jos{\'e} D. P. Rolim and David Steurer},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2018/9420},
  URN =		{urn:nbn:de:0030-drops-94205},
  doi =		{10.4230/LIPIcs.APPROX-RANDOM.2018.16},
  annote =	{Keywords: Approximation, Weighted Flow Time, Concurrent Open Shop, Precedence Constraints}
}

Keywords: Approximation, Weighted Flow Time, Concurrent Open Shop, Precedence Constraints
Collection: Approximation, Randomization, and Combinatorial Optimization. Algorithms and Techniques (APPROX/RANDOM 2018)
Issue Date: 2018
Date of publication: 13.08.2018


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