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Improving the Bounds of the Online Dynamic Power Management Problem

Authors Ya-Chun Liang, Kazuo Iwama, Chung-Shou Liao

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Author Details

Ya-Chun Liang
  • Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan
Kazuo Iwama
  • Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan
Chung-Shou Liao
  • Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan

Funding

  • Iwama, Kazuo: Supported by MOST Taiwan under Grants 110-2223-E-007-001, 110-2811-E-007-507 and KAKENHI Japan under Grant 16H02782.
  • Liao, Chung-Shou: Supported by MOST Taiwan under Grants 110-2221-E-007-106-MY3 and 110-2622-8-007-017.

Cite As Get BibTex

Ya-Chun Liang, Kazuo Iwama, and Chung-Shou Liao. Improving the Bounds of the Online Dynamic Power Management Problem. In 33rd International Symposium on Algorithms and Computation (ISAAC 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 248, pp. 28:1-28:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022) https://doi.org/10.4230/LIPIcs.ISAAC.2022.28

Abstract

We investigate the power-down mechanism which decides when a machine transitions between states such that the total energy consumption, characterized by execution cost, idle cost and switching cost, is minimized. In contrast to most of the previous studies on the offline model, we focus on the online model in which a sequence of jobs with their release time, execution time and deadline, arrive in an online fashion. More precisely, we exploit a different switching on and off strategy and present an upper bound of 3, and further show a lower bound of 2.1, in a dual-machine model, introduced by Chen et al. in 2014 [STACS 2014: 226-238], both of which beat the currently best result.

Subject Classification

ACM Subject Classification
  • Theory of computation → Design and analysis of algorithms
Keywords
  • Online algorithm
  • Energy scheduling
  • Dynamic power management

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