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Documents authored by Calinescu, Gruia

Document
DOI: 10.4230/LIPIcs.ESA.2024.37
Online Flexible Busy Time Scheduling on Heterogeneous Machines

Authors: Gruia Călinescu, Sami Davies, Samir Khuller, and Shirley Zhang

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
We study the online busy time scheduling model on heterogeneous machines. In our setting, jobs with uniform length arrive online with a deadline that becomes known to the algorithm at the job’s arrival time. An algorithm has access to machines, each with different associated capacities and costs. The goal is to schedule jobs on machines by their deadline, so that the total cost incurred by the scheduling algorithm is minimized. While busy time scheduling has been well-studied, relatively little is known when machines are heterogeneous (i.e., have different costs and capacities), despite this natural theoretical generalization being the most practical model for clients using cloud computing services. We make significant progress in understanding this model by designing an 8-competitive algorithm for the problem on unit-length jobs and provide a lower bound of 2 on the competitive ratio. The lower bound is tight in the setting when jobs form non-nested intervals. Our 8-competitive algorithm generalizes to one with competitive ratio 8(2p-1)/p < 16 when all jobs have uniform length p.
Cite as

Gruia Călinescu, Sami Davies, Samir Khuller, and Shirley Zhang. Online Flexible Busy Time Scheduling on Heterogeneous Machines. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 37:1-37:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{calinescu_et_al:LIPIcs.ESA.2024.37,
  author =	{C\u{a}linescu, Gruia and Davies, Sami and Khuller, Samir and Zhang, Shirley},
  title =	{{Online Flexible Busy Time Scheduling on Heterogeneous Machines}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{37:1--37:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.37},
  URN =		{urn:nbn:de:0030-drops-211083},
  doi =		{10.4230/LIPIcs.ESA.2024.37},
  annote =	{Keywords: Online algorithms, Scheduling, Competitive analysis}
}
Document
DOI: 10.4230/LIPIcs.ESA.2024.38
Local Optimization Algorithms for Maximum Planar Subgraph

Authors: Gruia Călinescu and Sumedha Uniyal

Published in: LIPIcs, Volume 308, 32nd Annual European Symposium on Algorithms (ESA 2024)

Abstract
Consider the NP-hard problem of, given a simple graph G, to find a planar subgraph of G with the maximum number of edges. This is called the Maximum Planar Subgraph problem and the best known approximation is 4/9 and is obtained by sophisticated Graphic Matroid Parity algorithms. Here we show that applying a local optimization phase to the output of this known algorithm improves this approximation ratio by a small {ε} = 1/747 > 0. This is the first improvement in approximation ratio in more than a quarter century. The analysis relies on a more refined extremal bound on the Lovász cactus number in planar graphs, compared to the earlier (tight) bound of [Gruia Călinescu et al., 1998; Chalermsook et al., 2019]. A second local optimization algorithm achieves a tight ratio of 5/12 for Maximum Planar Subgraph without using Graphic Matroid Parity. We also show that applying a greedy algorithm before this second optimization algorithm improves its ratio to at least 91/216 < 4/9. The motivation for not using Graphic Matroid Parity is that it requires sophisticated algorithms that are not considered practical by previous work. The best previously published [Chalermsook and Schmid, 2017] approximation ratio without Graphic Matroid Parity is 13/33 < 5/12.
Cite as

Gruia Călinescu and Sumedha Uniyal. Local Optimization Algorithms for Maximum Planar Subgraph. In 32nd Annual European Symposium on Algorithms (ESA 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 308, pp. 38:1-38:18, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)

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@InProceedings{calinescu_et_al:LIPIcs.ESA.2024.38,
  author =	{C\u{a}linescu, Gruia and Uniyal, Sumedha},
  title =	{{Local Optimization Algorithms for Maximum Planar Subgraph}},
  booktitle =	{32nd Annual European Symposium on Algorithms (ESA 2024)},
  pages =	{38:1--38:18},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-338-6},
  ISSN =	{1868-8969},
  year =	{2024},
  volume =	{308},
  editor =	{Chan, Timothy and Fischer, Johannes and Iacono, John and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2024.38},
  URN =		{urn:nbn:de:0030-drops-211090},
  doi =		{10.4230/LIPIcs.ESA.2024.38},
  annote =	{Keywords: planar graph, maximum subgraph, approximation algorithm, matroid parity, local optimization}
}
Document
DOI: 10.4230/LIPIcs.ISAAC.2017.19
An FPTAS of Minimizing Total Weighted Completion Time on Single Machine with Position Constraint

Authors: Gruia Calinescu, Florian Jaehn, Minming Li, and Kai Wang

Published in: LIPIcs, Volume 92, 28th International Symposium on Algorithms and Computation (ISAAC 2017)

Abstract
In this paper we study the classical scheduling problem of minimizing the total weighted completion time on a single machine with the constraint that one specific job must be scheduled at a specified position. We give dynamic programs with pseudo-polynomial running time, and a fully polynomial-time approximation scheme (FPTAS).
Cite as

Gruia Calinescu, Florian Jaehn, Minming Li, and Kai Wang. An FPTAS of Minimizing Total Weighted Completion Time on Single Machine with Position Constraint. In 28th International Symposium on Algorithms and Computation (ISAAC 2017). Leibniz International Proceedings in Informatics (LIPIcs), Volume 92, pp. 19:1-19:13, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)

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@InProceedings{calinescu_et_al:LIPIcs.ISAAC.2017.19,
  author =	{Calinescu, Gruia and Jaehn, Florian and Li, Minming and Wang, Kai},
  title =	{{An FPTAS of Minimizing Total Weighted Completion Time on Single Machine with Position Constraint}},
  booktitle =	{28th International Symposium on Algorithms and Computation (ISAAC 2017)},
  pages =	{19:1--19:13},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-054-5},
  ISSN =	{1868-8969},
  year =	{2017},
  volume =	{92},
  editor =	{Okamoto, Yoshio and Tokuyama, Takeshi},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ISAAC.2017.19},
  URN =		{urn:nbn:de:0030-drops-82335},
  doi =		{10.4230/LIPIcs.ISAAC.2017.19},
  annote =	{Keywords: FPTAS, Scheduling, Approximation Algorithm}
}
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