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ACM SIGACT News
Algorithmic problems in power management
ACM SIGACT News
Scheduling to minimize gaps and power consumption
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Speed scaling on parallel processors
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Energy-efficient algorithms for flow time minimization
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Competitive non-migratory scheduling for flow time and energy
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Sleep with Guilt and Work Faster to Minimize Flow Plus Energy
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Polynomial time algorithms for minimum energy scheduling
ESA'07 Proceedings of the 15th annual European conference on Algorithms
Scheduling to minimize power consumption using submodular functions
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Deadline scheduling and power management for speed bounded processors
Theoretical Computer Science
Adaptive power management for real-time event streams
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SIGACT news online algorithms column 17
ACM SIGACT News
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Energy-Efficient algorithms for flow time minimization
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Min-energy voltage allocation for tree-structured tasks
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Speed scaling to manage temperature
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Polynomial-time algorithms for minimum energy scheduling
ACM Transactions on Algorithms (TALG)
An online algorithm optimally self-tuning to congestion for power management problems
WAOA'11 Proceedings of the 9th international conference on Approximation and Online Algorithms
Optimal DPM and DVFS for frame-based real-time systems
ACM Transactions on Architecture and Code Optimization (TACO) - Special Issue on High-Performance Embedded Architectures and Compilers
Assessing Green Strategies in Peer-to-Peer Opportunistic Grids
Journal of Grid Computing
Scheduling to minimize gaps and power consumption
Journal of Scheduling
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We consider the problem of selecting threshold times to transition a device to low-power sleep states during an idle period. The two-state case in which there is a single active and a single sleep state is a continuous version of the ski-rental problem. We consider a generalized version in which there is more than one sleep state, each with its own power consumption rate and transition costs. We give an algorithm that, given a system, produces a deterministic strategy whose competitive ratio is arbitrarily close to optimal. We also give an algorithm to produce the optimal online strategy given a system and a probability distribution that generates the length of the idle period. We also give a simple algorithm that achieves a competitive ratio of 3 + 2\sqrt 2\approx 5.828 for any system.