Power-aware scheduling for makespan and flow

TL;DR

This paper develops efficient algorithms for energy-aware scheduling to optimize makespan and flow, revealing computational complexities and providing approximation methods for different processor and job scenarios.

Contribution

It introduces linear-time algorithms for non-dominated solutions in uniprocessor and homogeneous multiprocessor settings, and extends approximation techniques for flow scheduling.

Findings

Linear-time algorithms for non-dominated solutions in uniprocessor and homogeneous multiprocessor cases.

NP-hardness of multiprocessor scheduling with varying job work requirements.

Approximation algorithms for flow scheduling on multiprocessors.

Abstract

We consider offline scheduling algorithms that incorporate speed scaling to address the bicriteria problem of minimizing energy consumption and a scheduling metric. For makespan, we give linear-time algorithms to compute all non-dominated solutions for the general uniprocessor problem and for the multiprocessor problem when every job requires the same amount of work. We also show that the multiprocessor problem becomes NP-hard when jobs can require different amounts of work. For total flow, we show that the optimal flow corresponding to a particular energy budget cannot be exactly computed on a machine supporting arithmetic and the extraction of roots. This hardness result holds even when scheduling equal-work jobs on a uniprocessor. We do, however, extend previous work by Pruhs et al. to give an arbitrarily-good approximation for scheduling equal-work jobs on a multiprocessor.