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Scheduling equal-length jobs on identical parallel machines
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Algorithmic problems in power management
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Scheduling to minimize gaps and power consumption
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Scheduling to minimize power consumption using submodular functions
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Race to idle: new algorithms for speed scaling with a sleep state
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ACM Transactions on Algorithms (TALG)
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ESA'12 Proceedings of the 20th Annual European conference on Algorithms
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Scheduling to minimize gaps and power consumption
Journal of Scheduling
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Proceedings of the twenty-fifth annual ACM symposium on Parallelism in algorithms and architectures
Optimal procrastination interval for constrained deadline sporadic tasks upon uniprocessors
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Race to idle: New algorithms for speed scaling with a sleep state
ACM Transactions on Algorithms (TALG)
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Power Management policies aim at reducing the amount of energy consumed by battery operated systems, while keeping the overall performance high. In this paper we focus on shut-down mechanisms that put a system into a sleep state when it is idle. A very small amount of energy is consumed in this state but, a fixed amount of energy is required when moving the system from the sleep state to the active state. The offline version of this problem consists in scheduling a set of unit execution tasks, with release dates and deadlines, on a single machine in order to minimize the number of idle time periods. We show that this problem can be solved in polynomial time by Dynamic Programming.