Algorithms for Scheduling Imprecise Computations
Computer - Special issue on real-time systems
Algorithms for scheduling imprecise computations with timing constraints
SIAM Journal on Computing
IEEE Transactions on Computers
A scheduling model for reduced CPU energy
FOCS '95 Proceedings of the 36th Annual Symposium on Foundations of Computer Science
Optimal Reward-Based Scheduling of Periodic Real-Time Tasks
RTSS '99 Proceedings of the 20th IEEE Real-Time Systems Symposium
Maximizing the System Value while Satisfying Time and Energy Constraints
RTSS '02 Proceedings of the 23rd IEEE Real-Time Systems Symposium
Leakage aware dynamic voltage scaling for real-time embedded systems
Proceedings of the 41st annual Design Automation Conference
On Energy-Constrained Real-Time Scheduling
ECRTS '04 Proceedings of the 16th Euromicro Conference on Real-Time Systems
Voltage Scaling Scheduling for Periodic Real-Time Tasks in Reward Maximization
RTSS '05 Proceedings of the 26th IEEE International Real-Time Systems Symposium
Design considerations for solar energy harvesting wireless embedded systems
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Perpetual environmentally powered sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Everlast: long-life, supercapacitor-operated wireless sensor node
Proceedings of the 2006 international symposium on Low power electronics and design
Adaptive power management in energy harvesting systems
Proceedings of the conference on Design, automation and test in Europe
Power management in energy harvesting sensor networks
ACM Transactions on Embedded Computing Systems (TECS) - Special Section LCTES'05
Real-time scheduling for energy harvesting sensor nodes
Real-Time Systems
Energy-Efficient Scheduling for Real-Time Systems on Dynamic Voltage Scaling (DVS) Platforms
RTCSA '07 Proceedings of the 13th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
Proceedings of the 2007 IEEE/ACM international conference on Computer-aided design
Robust and low complexity rate control for solar powered sensors
Proceedings of the conference on Design, automation and test in Europe
Energy aware dynamic voltage and frequency selection for real-time systems with energy harvesting
Proceedings of the conference on Design, automation and test in Europe
Reward Maximization for Embedded Systems with Renewable Energies
RTCSA '08 Proceedings of the 2008 14th IEEE International Conference on Embedded and Real-Time Computing Systems and Applications
An energy management framework for energy harvesting embedded systems
ACM Journal on Emerging Technologies in Computing Systems (JETC)
Dynamic power management in environmentally powered systems
Proceedings of the 2010 Asia and South Pacific Design Automation Conference
Harvesting-aware power management for real-time systems with renewable energy
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
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Energy management is a critical concern in the design of embedded systems to prolong the lifetime or to maximize the performance under energy constraints. In particular, the emerging embedded systems with renewable energy sources rise new problems and trigger the revision of conventional energy management. If, e.g., the size of a solar cell limits the available power/energy of an electronic device, decisions like when to provide which service have to be made in order to satisfy the needs of the user as well as possible. In this paper, we explore how to maximize the system reward of diverse applications for an energy harvesting system. By utilizing the notion of rewards to express the different priorities of services, we answer the fundamental question of how to optimize the use of energy provided by a scarce and time-varying environmental source. For this purpose, we provide algorithms to optimally adjust service parameters dynamically. Our work is supported by simulation results which are based on long-term measurements of the power generated by real solar cells. Furthermore, we demonstrate how to dimension the embedded system, e.g., the battery capacity and elaborate on implementation details which are of practical importance.