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Energy-efficient scheduling and routing via randomized rounding

Author

Listed:
  • Evripidis Bampis

    (Sorbonne Universités, UPMC Univ Paris 06)

  • Alexander Kononov

    (Sobolev Institute of Mathematics)

  • Dimitrios Letsios

    (Sorbonne Universités, UPMC Univ Paris 06
    Univ. Nice Sophia Antipolis)

  • Giorgio Lucarelli

    (Sorbonne Universités, UPMC Univ Paris 06
    Grenoble INP)

  • Maxim Sviridenko

    (Yahoo Labs)

Abstract

We propose a unifying framework based on configuration linear programs and randomized rounding, for different energy optimization problems in the dynamic speed-scaling setting. We apply our framework to various scheduling and routing problems in heterogeneous computing and networking environments. We first consider the energy minimization problem of scheduling a set of jobs on a set of parallel speed scalable processors in a fully heterogeneous setting. For both the preemptive-nonmigratory and the preemptive-migratory variants, our approach allows us to obtain solutions of almost the same quality as for the homogeneous environment. By exploiting the result for the preemptive-nonmigratory variant, we are able to improve the best known approximation ratio for the single processor non-preemptive problem. Furthermore, we show that our approach allows to obtain a constant-factor approximation algorithm for the power-aware preemptive job shop scheduling problem. Finally, we consider the min-power routing problem where we are given a network modeled by an undirected graph and a set of uniform demands that have to be routed on integral routes from their sources to their destinations so that the energy consumption is minimized. We improve the best known approximation ratio for this problem.

Suggested Citation

  • Evripidis Bampis & Alexander Kononov & Dimitrios Letsios & Giorgio Lucarelli & Maxim Sviridenko, 2018. "Energy-efficient scheduling and routing via randomized rounding," Journal of Scheduling, Springer, vol. 21(1), pages 35-51, February.
    • Handle: RePEc:spr:jsched:v:21:y:2018:i:1:d:10.1007_s10951-016-0500-2
    DOI: 10.1007/s10951-016-0500-2
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    References listed on IDEAS

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    1. Marco E. T. Gerards & Johann L. Hurink & Philip K. F. Hölzenspies, 2016. "A survey of offline algorithms for energy minimization under deadline constraints," Journal of Scheduling, Springer, vol. 19(1), pages 3-19, February.
    2. Nan Zhang & Hong He & Shao Zhang & Xiao Jiang & Zi Xia & Feng Huang, 2012. "Influence of Reservoir Operation in the Upper Reaches of the Yangtze River (China) on the Inflow and Outflow Regime of the TGR-based on the Improved SWAT Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(3), pages 691-705, February.
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    Cited by:

    1. Alexander Kononov & Yulia Zakharova, 2022. "Speed scaling scheduling of multiprocessor jobs with energy constraint and makespan criterion," Journal of Global Optimization, Springer, vol. 83(3), pages 539-564, July.
    2. Alexander Kononov & Yulia Kovalenko, 2020. "Approximation algorithms for energy-efficient scheduling of parallel jobs," Journal of Scheduling, Springer, vol. 23(6), pages 693-709, December.

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