Slow Down & Sleep for Profit in Online Deadline Scheduling
Peter Kling, Andreas Cord-Landwehr, Frederik Mallmann-Trenn

TL;DR
This paper introduces a new energy-aware, profit-oriented scheduling model with dynamic speed scaling and sleep modes, analyzing the competitiveness of rejection-oblivious algorithms and proposing near-optimal solutions.
Contribution
It combines energy conservation techniques with profit-driven scheduling and provides bounds and algorithms for rejection-oblivious schedulers in this context.
Findings
Rejection-oblivious schedulers have unbounded competitive ratios with sleep states.
The worst-case performance depends linearly on job value densities.
Proposed algorithms nearly match the theoretical lower bounds.
Abstract
We present and study a new model for energy-aware and profit-oriented scheduling on a single processor. The processor features dynamic speed scaling as well as suspension to a sleep mode. Jobs arrive over time, are preemptable, and have different sizes, values, and deadlines. On the arrival of a new job, the scheduler may either accept or reject the job. Accepted jobs need a certain energy investment to be finished in time, while rejected jobs cause costs equal to their values. Here, power consumption at speed is given by and the energy investment is power integrated over time. Additionally, the scheduler may decide to suspend the processor to a sleep mode in which no energy is consumed, though awaking entails fixed transition costs . The objective is to minimize the total value of rejected jobs plus the total energy. Our model combines aspects from…
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Taxonomy
TopicsCloud Computing and Resource Management · Parallel Computing and Optimization Techniques · Stochastic Gradient Optimization Techniques
