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O(1/ε) Is the Answer in Online Weighted Throughput Maximization

Author Franziska Eberle

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LIPIcs.STACS.2024.32.pdf
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Author Details

Franziska Eberle
  • Technische Universität Berlin, Germany

Funding

Supported by the Dutch Research Council (NWO), Netherlands Vidi grant 016.Vidi.189.087.

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Franziska Eberle. O(1/ε) Is the Answer in Online Weighted Throughput Maximization. In 41st International Symposium on Theoretical Aspects of Computer Science (STACS 2024). Leibniz International Proceedings in Informatics (LIPIcs), Volume 289, pp. 32:1-32:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2024)
https://doi.org/10.4230/LIPIcs.STACS.2024.32

Abstract

We study a fundamental online scheduling problem where jobs with processing times, weights, and deadlines arrive online over time at their release dates. The task is to preemptively schedule these jobs on a single or multiple (possibly unrelated) machines with the objective to maximize the weighted throughput, the total weight of jobs that complete before their deadline. To overcome known lower bounds for the competitive analysis, we assume that each job arrives with some slack ε > 0; that is, the time window for processing job j on any machine i on which it can be executed has length at least (1+ε) times j’s processing time on machine i. Our contribution is a best possible online algorithm for weighted throughput maximization on unrelated machines: Our algorithm is 𝒪(1/ε)-competitive, which matches the lower bound for unweighted throughput maximization on a single machine. Even for a single machine, it was not known whether the problem with weighted jobs is "harder" than the problem with unweighted jobs. Thus, we answer this question and close weighted throughput maximization on a single machine with a best possible competitive ratio Θ(1/ε). While we focus on non-migratory schedules, on identical machines, our algorithm achieves the same (up to constants) performance guarantee when compared to an optimal migratory schedule.

Subject Classification

ACM Subject Classification
  • Theory of computation → Online algorithms
  • Theory of computation → Scheduling algorithms
Keywords
  • Deadline scheduling
  • weighted throughput
  • online algorithms
  • competitive analysis

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