A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Dynamic Speed Scaling to Manage Energy and Temperature
FOCS '04 Proceedings of the 45th Annual IEEE Symposium on Foundations of Computer Science
Algorithmic problems in power management
ACM SIGACT News
Power-aware scheduling for makespan and flow
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
Energy-Efficient algorithms for flow time minimization
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Competitive online scheduling for server systems
ACM SIGMETRICS Performance Evaluation Review
Energy-efficient algorithms for flow time minimization
ACM Transactions on Algorithms (TALG)
Competitive non-migratory scheduling for flow time and energy
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Speed Scaling with a Solar Cell
AAIM '08 Proceedings of the 4th international conference on Algorithmic Aspects in Information and Management
Speed Scaling Functions for Flow Time Scheduling Based on Active Job Count
ESA '08 Proceedings of the 16th annual European symposium on Algorithms
Speed scaling with an arbitrary power function
SODA '09 Proceedings of the twentieth Annual ACM-SIAM Symposium on Discrete Algorithms
Non-clairvoyant speed scaling for batched parallel jobs on multiprocessors
Proceedings of the 6th ACM conference on Computing frontiers
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
Sleep with Guilt and Work Faster to Minimize Flow Plus Energy
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Speed scaling of processes with arbitrary speedup curves on a multiprocessor
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
The bell is ringing in speed-scaled multiprocessor scheduling
Proceedings of the twenty-first annual symposium on Parallelism in algorithms and architectures
Speed scaling with a solar cell
Theoretical Computer Science
Optimal speed scaling under arbitrary power functions
ACM SIGMETRICS Performance Evaluation Review
Optimizing throughput and energy in online deadline scheduling
ACM Transactions on Algorithms (TALG)
Power-aware scheduling for makespan and flow
Journal of Scheduling
Min-Energy Scheduling for Aligned Jobs in Accelerate Model
ISAAC '09 Proceedings of the 20th International Symposium on Algorithms and Computation
Communications of the ACM
Online deadline scheduling with bounded energy efficiency
TAMC'07 Proceedings of the 4th international conference on Theory and applications of models of computation
Energy efficient deadline scheduling in two processor systems
ISAAC'07 Proceedings of the 18th international conference on Algorithms and computation
On temperature-aware scheduling for single-processor systems
HiPC'07 Proceedings of the 14th international conference on High performance computing
Optimality, fairness, and robustness in speed scaling designs
Proceedings of the ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Distributed dynamic speed scaling
INFOCOM'10 Proceedings of the 29th conference on Information communications
Deadline scheduling and power management for speed bounded processors
Theoretical Computer Science
Non-clairvoyant scheduling for weighted flow time and energy on speed bounded processors
CATS '10 Proceedings of the Sixteenth Symposium on Computing: the Australasian Theory - Volume 109
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
Min-energy scheduling for aligned jobs in accelerate model
Theoretical Computer Science
Tradeoff between energy and throughput for online deadline scheduling
WAOA'10 Proceedings of the 8th international conference on Approximation and online algorithms
Energy-efficient due date scheduling
TAPAS'11 Proceedings of the First international ICST conference on Theory and practice of algorithms in (computer) systems
Speed scaling for energy and performance with instantaneous parallelism
TAPAS'11 Proceedings of the First international ICST conference on Theory and practice of algorithms in (computer) systems
Minimizing energy cost for internet-scale datacenters with dynamic traffic
Proceedings of the Nineteenth International Workshop on Quality of Service
Multiprocessor speed scaling for jobs with arbitrary sizes and deadlines
TAMC'11 Proceedings of the 8th annual conference on Theory and applications of models of computation
Improved multi-processor scheduling for flow time and energy
Journal of Scheduling
Algorithms for energy management
CSR'10 Proceedings of the 5th international conference on Computer Science: theory and Applications
Power-aware speed scaling in processor sharing systems: Optimality and robustness
Performance Evaluation
Speed Scaling with an Arbitrary Power Function
ACM Transactions on Algorithms (TALG)
Decoupled speed scaling: Analysis and evaluation
Performance Evaluation
The Bell Is Ringing in Speed-Scaled Multiprocessor Scheduling
Theory of Computing Systems
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In addition to the traditional goal of efficiently managing time and space, many computers now need to efficiently manage power usage. For example, Intel's SpeedStep and AMD's PowerNOW technologies allow the Windows XP operating system to dynamically change the speed of the processor to prolong battery life. In this setting, the operating system must not only have a job selection policy to determine which job to run, but also a speed scaling policy to determine the speed at which the job will be run. These policies must be online since the operating system does not in general have knowledge of the future. In current CMOS based processors, the speed satisfies the well known cube-root-rule, that the speed is approximately the cube root of the power [Mud01, BBS+00]. Thus, in this work, we make the standard generalization that the power is equal to speed to some power α ≥ 1, where one should think of α as being approximately 3 [YDS95, BKP04]. Energy is power integrated over time. The operating system is faced with a dual objective optimization problem as it both wants to conserve energy, and optimize some Quality of Service (QoS) measure of the resulting schedule.