Optimal voltage allocation techniques for dynamically variable voltage processors
Proceedings of the 40th annual Design Automation Conference
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Online strategies for dynamic power management in systems with multiple power-saving states
ACM Transactions on Embedded Computing Systems (TECS)
On energy-optimal voltage scheduling for fixed-priority hard real-time systems
ACM Transactions on Embedded Computing Systems (TECS)
Convex Optimization
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
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
ACM Transactions on Algorithms (TALG)
LATIN'08 Proceedings of the 8th Latin American conference on Theoretical informatics
Speed scaling to manage temperature
STACS'05 Proceedings of the 22nd annual conference on Theoretical Aspects of Computer Science
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We consider the setting of a device that obtains its energy from a battery and some regenerative source such as a solar cell. We consider the speed scaling problem of scheduling a collection of tasks with release times, deadlines, and sizes, so as to minimize the energy recharge rate of the regenerative source. This is the first theoretical investigation of speed scaling for devices with a regenerative energy source. We show that the problem can be expressed as a polynomial sized convex program. We show that, using the KKT conditions, one can obtain an efficient algorithm to verify the optimality of a schedule. We show that the energy optimal YDS schedule is 2-approximate with respect to the recharge rate. We show that the online algorithm BKP is O(1)-competitive with respect to recharge rate.