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Scheduling Distributed Clusters of Parallel Machines: Primal-Dual and LP-based Approximation Algorithms

Authors: Riley Murray, Megan Chao, and Samir Khuller

Published in: LIPIcs, Volume 57, 24th Annual European Symposium on Algorithms (ESA 2016)


Abstract
The Map-Reduce computing framework rose to prominence with datasets of such size that dozens of machines on a single cluster were needed for individual jobs. As datasets approach the exabyte scale, a single job may need distributed processing not only on multiple machines, but on multiple clusters. We consider a scheduling problem to minimize weighted average completion time of n jobs on m distributed clusters of parallel machines. In keeping with the scale of the problems motivating this work, we assume that (1) each job is divided into m "subjobs" and (2) distinct subjobs of a given job may be processed concurrently. When each cluster is a single machine, this is the NP-Hard concurrent open shop problem. A clear limitation of such a model is that a serial processing assumption sidesteps the issue of how different tasks of a given subjob might be processed in parallel. Our algorithms explicitly model clusters as pools of resources and effectively overcome this issue. Under a variety of parameter settings, we develop two constant factor approximation algorithms for this problem. The first algorithm uses an LP relaxation tailored to this problem from prior work. This LP-based algorithm provides strong performance guarantees. Our second algorithm exploits a surprisingly simple mapping to the special case of one machine per cluster. This mapping-based algorithm is combinatorial and extremely fast. These are the first constant factor approximations for this problem.

Cite as

Riley Murray, Megan Chao, and Samir Khuller. Scheduling Distributed Clusters of Parallel Machines: Primal-Dual and LP-based Approximation Algorithms. In 24th Annual European Symposium on Algorithms (ESA 2016). Leibniz International Proceedings in Informatics (LIPIcs), Volume 57, pp. 68:1-68:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2016)


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@InProceedings{murray_et_al:LIPIcs.ESA.2016.68,
  author =	{Murray, Riley and Chao, Megan and Khuller, Samir},
  title =	{{Scheduling Distributed Clusters of Parallel Machines: Primal-Dual and LP-based Approximation Algorithms}},
  booktitle =	{24th Annual European Symposium on Algorithms (ESA 2016)},
  pages =	{68:1--68:17},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-015-6},
  ISSN =	{1868-8969},
  year =	{2016},
  volume =	{57},
  editor =	{Sankowski, Piotr and Zaroliagis, Christos},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops-dev.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2016.68},
  URN =		{urn:nbn:de:0030-drops-64104},
  doi =		{10.4230/LIPIcs.ESA.2016.68},
  annote =	{Keywords: approximation algorithms, distributed computing, machine scheduling, LP relaxations, primal-dual algorithms}
}
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