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Scheduling on Power-Heterogeneous Processors


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.
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hal-01366481 , version 1 (14-09-2016)



Susanne Albers, Evripidis Bampis, Dimitrios Letsios, Giorgio Lucarelli, Stotz Richard. Scheduling on Power-Heterogeneous Processors. LATIN 2016: Theoretical Informatics, Apr 2016, Ensenada, Mexico. pp.41-54, ⟨10.1007/978-3-662-49529-2_4⟩. ⟨hal-01366481⟩
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