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Improved Online Load Balancing with Known Makespan

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F24%3A10491729" target="_blank" >RIV/00216208:11320/24:10491729 - isvavai.cz</a>

  • Result on the web

    <a href="https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2024.10" target="_blank" >https://doi.org/10.4230/LIPIcs.APPROX/RANDOM.2024.10</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.4230/LIPIcs.APPROX/RANDOM.2024.10" target="_blank" >10.4230/LIPIcs.APPROX/RANDOM.2024.10</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Improved Online Load Balancing with Known Makespan

  • Original language description

    We break the barrier of 3/2 for the problem of online load balancing with known makespan, also known as bin stretching. In this problem, m identical machines and the optimal makespan are given. The load of a machine is the total size of all the jobs assigned to it and the makespan is the maximum load of all the machines. Jobs arrive online and the goal is to assign each job to a machine while staying within a small factor (the competitive ratio) of the optimal makespan. We present an algorithm that maintains a competitive ratio of 139/93 &lt; 1.495 for sufficiently large values of m, improving the previous bound of 3/2. The value 3/2 represents a natural bound for this problem: as long as the online bins are of size at least 3/2 of the offline bin, all items that fit at least two times in an offline bin have two nice properties. They fit three times in an online bin and a single such item can be packed together with an item of any size in an online bin. These properties are now both lost, which means that putting even one job on a wrong machine can leave some job unassigned at the end. It also makes it harder to determine good thresholds for the item types. This was one of the main technical issues in getting below 3/2. The analysis consists of an intricate mixture of size and weight arguments. (C) Martin Böhm, Matej Lieskovský, Sören Schmitt, Jiří Sgall, and Rob van Stee.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GA24-10306S" target="_blank" >GA24-10306S: New challenges in streaming, online, and combinatorial algorithms</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Others

  • Publication year

    2024

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Leibniz International Proceedings in Informatics, LIPIcs

  • ISBN

    978-3-95977-348-5

  • ISSN

    1868-8969

  • e-ISSN

  • Number of pages

    21

  • Pages from-to

  • Publisher name

    Schloss Dagstuhl- Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing

  • Place of publication

    Germany

  • Event location

    London

  • Event date

    Aug 28, 2024

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article