Online scheduling with hard deadlines
Journal of Algorithms
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
SODA '03 Proceedings of the fourteenth annual ACM-SIAM symposium on Discrete algorithms
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
Optimal voltage allocation techniques for dynamically variable voltage processors
ACM Transactions on Embedded Computing Systems (TECS)
Algorithmic problems in power management
ACM SIGACT News
An Efficient Algorithm for Computing Optimal Discrete Voltage Schedules
SIAM Journal on Computing
Power-aware scheduling for makespan and flow
Proceedings of the eighteenth annual ACM symposium on Parallelism in algorithms and architectures
Policies for dynamic clock scheduling
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Scheduling for reduced CPU energy
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
Energy efficient online deadline scheduling
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Speed scaling for weighted flow time
SODA '07 Proceedings of the eighteenth annual ACM-SIAM symposium on Discrete algorithms
Energy-Efficient algorithms for flow time minimization
STACS'06 Proceedings of the 23rd Annual conference on Theoretical Aspects of Computer Science
Speed scaling of tasks with precedence constraints
WAOA'05 Proceedings of the Third international conference on Approximation and Online Algorithms
Min-energy voltage allocation for tree-structured tasks
COCOON'05 Proceedings of the 11th annual international conference on Computing and Combinatorics
Speed scaling to manage temperature
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
Min-energy scheduling for aligned jobs in accelerate model
Theoretical Computer Science
Proceedings of the 3rd International Conference on Future Energy Systems: Where Energy, Computing and Communication Meet
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Existing work on scheduling with energy concern has focused on minimizing the energy for completing all jobs or achieving maximum throughput [19, 2,7,13,14]. That is, energy usage is a secondary concern when compared to throughput and the schedules targeted may be very poor in energy efficiency. In this paper, we attempt to put energy efficiency as the primary concern and study how to maximize throughput subject to a user-defined threshold of energy efficiency. We first show that all deterministic online algorithms have a competitive ratio at least Δ, where Δ is the max-min ratio of job size. Nevertheless, allowing the online algorithm to have a slightly poorer energy efficiency leads to constant (i.e., independent of Δ) competitive online algorithm. On the other hand, using randomization, we can reduce the competitive ratio to O(logΔ) without relaxing the efficiency threshold. Finally we consider a special case where no jobs are "demanding" and give a deterministic online algorithm with constant competitive ratio for this case.