10.1145/2486159.2486183
Kling, Peter
Peter
Kling
Pietrzyk, Peter
Peter
Pietrzyk
Profitable Scheduling on Multiple Speed-Scalable Processors
2013
2017-10-17T12:42:29Z
2019-04-11T14:21:38Z
conference
https://ris.uni-paderborn.de/record/499
https://ris.uni-paderborn.de/record/499.json
558661 bytes
application/pdf
We present a new online algorithm for profit-oriented scheduling on multiple speed-scalable processors.Moreover, we provide a tight analysis of the algorithm's competitiveness.Our results generalize and improve upon work by \citet{Chan:2010}, which considers a single speed-scalable processor.Using significantly different techniques, we can not only extend their model to multiprocessors but also prove an enhanced and tight competitive ratio for our algorithm.In our scheduling problem, jobs arrive over time and are preemptable.They have different workloads, values, and deadlines.The scheduler may decide not to finish a job but instead to suffer a loss equaling the job's value.However, to process a job's workload until its deadline the scheduler must invest a certain amount of energy.The cost of a schedule is the sum of lost values and invested energy.In order to finish a job the scheduler has to determine which processors to use and set their speeds accordingly.A processor's energy consumption is power $\Power{s}$ integrated over time, where $\Power{s}=s^{\alpha}$ is the power consumption when running at speed $s$.Since we consider the online variant of the problem, the scheduler has no knowledge about future jobs.This problem was introduced by~\citet{Chan:2010} for the case of a single processor.They presented an online algorithm which is $\alpha^{\alpha}+2e\alpha$-competitive.We provide an online algorithm for the case of multiple processors with an improved competitive ratio of $\alpha^{\alpha}$.