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Symmetry Exploitation for Online Machine Covering with Bounded Migration

Published: 06 July 2020 Publication History

Abstract

Online models that allow recourse can be highly effective in situations where classical online models are too pessimistic. One such problem is the online machine covering problem on identical machines. In this setting, jobs arrive one by one and must be assigned to machines with the objective of maximizing the minimum machine load. When a job arrives, we are allowed to reassign some jobs as long as their total size is (at most) proportional to the processing time of the arriving job. The proportionality constant is called the migration factor of the algorithm.
Using a rounding procedure with useful structural properties for online packing and covering problems, we design first a simple (1.7 + ε)-competitive algorithm using a migration factor of O(1/ε), which maintains at every arrival a locally optimal solution with respect to the Jump neighborhood. After that, we present as our main contribution a more involved (4/3+ε)-competitive algorithm using a migration factor of Ō(1/ε 3). At every arrival, we run an adaptation of the Largest Processing Time first (LPT) algorithm. Since the new job can cause a complete change of the assignment of smaller jobs in both cases, a low migration factor is achieved by carefully exploiting the highly symmetric structure obtained by the rounding procedure.

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      cover image ACM Transactions on Algorithms
      ACM Transactions on Algorithms  Volume 16, Issue 4
      October 2020
      404 pages
      ISSN:1549-6325
      EISSN:1549-6333
      DOI:10.1145/3407674
      Issue’s Table of Contents
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      Publication History

      Published: 06 July 2020
      Online AM: 07 May 2020
      Accepted: 01 April 2020
      Revised: 01 April 2020
      Received: 01 April 2019
      Published in TALG Volume 16, Issue 4

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      Author Tags

      1. LPT
      2. Machine covering
      3. bounded migration
      4. online
      5. scheduling

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      • Comisión Nacional de Investigación Científica y Tecnológica
      • Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung

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