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.

Authors

• Susanne Albers
• Evripidis Bampis
• Dimitrios Letsios
• Giorgio Lucarelli
• Richard Stotz

Keywords

• Heterogeneous processors
• Scheduling
• Speed-scaling
• Energy
• Approximation algorithms
• Online algorithms