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Scheduling on Power-Heterogeneous Processors

Part of the Lecture Notes in Computer Science book series (LNTCS,volume 9644)

Abstract

We consider the problem of scheduling a set of jobs, each one specified by its release date, its deadline and its processing volume, on a set of heterogeneous speed-scalable processors, where the energy-consumption rate is processor-dependent. Our objective is to minimize the total energy consumption when both the preemption and the migration of jobs are allowed. We propose a new algorithm based on a compact linear programming formulation. Our method approaches the value of the optimal solution within any desired accuracy for a large set of continuous power functions. Furthermore, we develop a faster combinatorial algorithm based on flows for standard power functions and jobs whose density is lower bounded by a small constant. Finally, we extend and analyze the AVerage Rate (AVR) online algorithm in the heterogeneous setting.

Keywords

  • Power Function
  • Optimal Schedule
  • Competitive Ratio
  • Feasible Schedule
  • Earliest Deadline First

These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

S. Albers—Work supported by the German Research Foundation, projects Al 464/ 7-1 and Al 464/9-1.

E. Bampis—Research partially supported by projet GDR-RO AGaPe of CNRS.

D. Letsios—Research partially supported by ANR project Stint and ANR program “Investments for the Future”.

G. Lucarelli—Research supported by projet ANR Moebus.

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Correspondence to Giorgio Lucarelli .

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Albers, S., Bampis, E., Letsios, D., Lucarelli, G., Stotz, R. (2016). Scheduling on Power-Heterogeneous Processors. In: Kranakis, E., Navarro, G., Chávez, E. (eds) LATIN 2016: Theoretical Informatics. LATIN 2016. Lecture Notes in Computer Science(), vol 9644. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-49529-2_4

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  • DOI: https://doi.org/10.1007/978-3-662-49529-2_4

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