Journal of Scheduling

, Volume 21, Issue 1, pp 35–51 | Cite as

Energy-efficient scheduling and routing via randomized rounding

  • Evripidis Bampis
  • Alexander Kononov
  • Dimitrios Letsios
  • Giorgio LucarelliEmail author
  • Maxim Sviridenko


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.


Randomized rounding Scheduling Approximation Energy-aware Configuration linear program 



We would like to thank Oleg Pikhurko for providing the original proof of Part (b) of the Proposition 6.


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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Evripidis Bampis
    • 1
  • Alexander Kononov
    • 2
  • Dimitrios Letsios
    • 1
    • 3
  • Giorgio Lucarelli
    • 1
    • 4
    Email author
  • Maxim Sviridenko
    • 5
  1. 1.LIP6, UMR 7606Sorbonne Universités, UPMC Univ Paris 06ParisFrance
  2. 2.Sobolev Institute of MathematicsNovosibirskRussia
  3. 3.I3S, UMR 7271Univ. Nice Sophia AntipolisSophia AntipolisFrance
  4. 4.LIG, UMR 5217Grenoble INPGrenobleFrance
  5. 5.Yahoo LabsNew YorkUSA

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