Battery-aware static scheduling for distributed real-time embedded systems
Proceedings of the 38th annual Design Automation Conference
Discrete-time battery models for system-level low-power design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Battery-Driven Dynamic Power Management
IEEE Design & Test
Battery-aware power management based on Markovian decision processes
Proceedings of the 2002 IEEE/ACM international conference on Computer-aided design
Energy management for battery-powered embedded systems
ACM Transactions on Embedded Computing Systems (TECS)
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
Balancing batteries, power, and performance: system issues in cpu speed-setting for mobile computing
An Analytical Model for Predicting the Remaining Battery Capacity of Lithium-Ion Batteries
DATE '03 Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
An Iterative Algorithm for Battery-Aware Task Scheduling on Portable Computing Platforms
Proceedings of the conference on Design, Automation and Test in Europe - Volume 1
Battery-powered digital CMOS design
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Energy efficient battery management
IEEE Journal on Selected Areas in Communications
Hardware based frequency/voltage control of voltage frequency island systems
CODES+ISSS '06 Proceedings of the 4th international conference on Hardware/software codesign and system synthesis
ACM Transactions on Design Automation of Electronic Systems (TODAES)
IntellBatt: towards smarter battery design
Proceedings of the 45th annual Design Automation Conference
Energy budget approximations for battery-powered systems with a fixed schedule of active intervals
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
System-level integrated power management for handheld systems
Microprocessors & Microsystems
Near optimal battery-aware energy management
Proceedings of the 14th ACM/IEEE international symposium on Low power electronics and design
Power management of voltage/frequency island-based systems using hardware-based methods
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
Enhancing battery efficiency for pervasive health-monitoring systems based on electronic textiles
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
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Batteries are non-ideal energy sources - minimizing the energy consumption of a battery-powered system is not equivalent to maximizing its battery life. We propose an alternative interpretation of a previously proposed battery model, which indicates that the deviation from ideal behavior is due to the buildup of "unavailable charge" during the discharge process. Previously, battery-aware task scheduling algorithms and power management policies have been developed, which try to reduce the unavailable charge at the end of a given workload. However, they do not account for the occurrence of rest periods (user enforced, naturally occurring, or due to finite load horizon), which are present in a variety of workloads. We first obtain an analytical bound on the recovery time of a battery as a function of the extent of recovery. Then, we shown that the effect of the rest periods is to reduce the improvement of battery-charge optimizing techniques over traditional energy-optimizing techniques. Under certain conditions, the policy that only minimizes energy consumption can actually achieve a longer battery lifetime than a battery-aware policy. A formal criterion based on the recovery time is proposed to choose between a candidate battery-aware policy and a candidate energy-aware policy. We also model the battery discharge process as a linear time invariant system and obtain the frequency response of a battery. This is then used to study the effect of task granularity on the improvement achieved by battery-aware task scheduling. It was observed that the response time of typical batteries are of the order of seconds to several minutes. This, along with the charge recovery effect, was seen to cause battery-aware task scheduling methods to become ineffective for both very fine-grained (less than 10 ms) and very coarse-grained (greater than 30 mm) task granularities.