Amortized efficiency of list update and paging rules
Communications of the ACM
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
An Efficient Algorithm for Computing Optimal Discrete Voltage Schedules
SIAM Journal on Computing
Speed scaling to manage energy and temperature
Journal of the ACM (JACM)
Speed scaling on parallel processors
Proceedings of the nineteenth annual ACM symposium on Parallel algorithms and architectures
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
Energy Optimal Scheduling on Multiprocessors with Migration
ISPA '08 Proceedings of the 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications
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
The bell is ringing in speed-scaled multiprocessor scheduling
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Energy efficient deadline scheduling in two processor systems
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Speed scaling on parallel processors with migration
Euro-Par'12 Proceedings of the 18th international conference on Parallel Processing
Slow down and sleep for profit in online deadline scheduling
MedAlg'12 Proceedings of the First Mediterranean conference on Design and Analysis of Algorithms
Profitable scheduling on multiple speed-scalable processors
Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
Online parallel scheduling of non-uniform tasks: trading failures for energy
FCT'13 Proceedings of the 19th international conference on Fundamentals of Computation Theory
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We investigate a very basic problem in dynamic speed scaling where a sequence of jobs, each specified by an arrival time, a deadline and a processing volume, has to be processed so as to minimize energy consumption. Previous work has focused mostly on the setting where a single variable-speed processor is available. In this paper we study multi-processor environments with m parallel variable-speed processors assuming that job migration is allowed, i.e. whenever a job is preempted it may be moved to a different processor. We first study the offline problem and show that optimal schedules can be computed efficiently in polynomial time. In contrast to a previously known strategy, our algorithm does not resort to linear programming. We develop a fully combinatorial algorithm that relies on repeated maximum flow computations. The approach might be useful to solve other problems in dynamic speed scaling. For the online problem, we extend two algorithms Optimal Available and Average Rate proposed by Yao et al. [16] for the single processor setting. We prove that Optimal Available is αα-competitive, as in the single processor case. Here α1 is the exponent of the power consumption function. While it is straightforward to extend Optimal Available to parallel processing environments, the competitive analysis becomes considerably more involved. For Average Rate we show a competitiveness of (3\α)α/2 + 2α.