On-line scheduling in the presence of overload
SFCS '91 Proceedings of the 32nd annual symposium on Foundations of computer science
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
SODA '06 Proceedings of the seventeenth annual ACM-SIAM symposium on Discrete algorithm
Speed scaling to manage energy and temperature
Journal of the ACM (JACM)
Energy efficient online deadline scheduling
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
ACM Transactions on Algorithms (TALG)
Scheduling for Speed Bounded Processors
ICALP '08 Proceedings of the 35th international colloquium on Automata, Languages and Programming, Part I
Improved Bounds for Speed Scaling in Devices Obeying the Cube-Root Rule
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Communications of the ACM
Polynomial time algorithms for minimum energy scheduling
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Deadline scheduling and power management for speed bounded processors
Theoretical Computer Science
How to schedule when you have to buy your energy
APPROX/RANDOM'10 Proceedings of the 13th international conference on Approximation, and 14 the International conference on Randomization, and combinatorial optimization: algorithms and techniques
Tradeoff between energy and throughput for online deadline scheduling
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
On multi-processor speed scaling with migration: extended abstract
Proceedings of the twenty-third annual ACM symposium on Parallelism in algorithms and architectures
Race to idle: new algorithms for speed scaling with a sleep state
Proceedings of the twenty-third annual ACM-SIAM symposium on Discrete Algorithms
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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 s is given by P(s)=sα+β 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 γ. The objective is to minimize the total value of rejected jobs plus the total energy. Our model combines aspects from advanced energy conservation techniques (namely speed scaling and sleep states) and profit-oriented scheduling models. We show that rejection-oblivious schedulers (whose rejection decisions are not based on former decisions) have - in contrast to the model without sleep states - an unbounded competitive ratio w.r.t. the processor parameters α and β. It turns out that the worst-case performance of such schedulers depends linearly on the jobs' value densities (the ratio between a job's value and its work). We give an algorithm whose competitiveness nearly matches this lower bound. If the maximum value density is not too large, the competitiveness becomes αα+2eα. Also, we show that it suffices to restrict the value density of low-value jobs only. Using a technique from [13] we transfer our results to processors with a fixed maximum speed.