Voltage scheduling problem for dynamically variable voltage processors
ISLPED '98 Proceedings of the 1998 international symposium on Low power electronics and design
Battery-aware static scheduling for distributed real-time embedded systems
Proceedings of the 38th annual Design Automation Conference
Approximation algorithms
Real-time dynamic voltage scaling for low-power embedded operating systems
SOSP '01 Proceedings of the eighteenth ACM symposium on Operating systems principles
Optimal Control Systems
Battery-Driven Dynamic Power Management
IEEE Design & Test
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Energy management for battery-powered embedded systems
ACM Transactions on Embedded Computing Systems (TECS)
Proceedings of the conference on Design, automation and test in Europe
Battery optimization vs energy optimization: which to choose and when?
ICCAD '05 Proceedings of the 2005 IEEE/ACM International conference on Computer-aided design
Static task-scheduling algorithms for battery-powered DVS systems
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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The paper addresses the problem of battery lifetime maximization for a job sequence executing on a processor with discrete voltage/frequency states under a deadline constraint. We consider a nonlinear electrochemical discharging model of the battery, and present a pseudo-polynomial time optimal algorithm and a fully polynomial time approximation algorithm as solutions. This is the first work that proposes both optimal and approximation algorithms for battery aware energy management based on voltage/frequency scaling techniques. Our experimental results show that the approximation algorithms widely outperform an existing technique. Further, for a number of realistic and synthetic benchmarks, the qualities of the solutions produced by our approximation techniques are much better than the required quality bounds imposed by the designer.