Resource allocation problems: algorithmic approaches
Resource allocation problems: algorithmic approaches
Next century challenges: scalable coordination in sensor networks
MobiCom '99 Proceedings of the 5th annual ACM/IEEE international conference on Mobile computing and networking
The impact of battery capacity and memory bandwidth on CPU speed-setting: a case study
ISLPED '99 Proceedings of the 1999 international symposium on Low power electronics and design
Algorithmic transforms for efficient energy scalable computation
ISLPED '00 Proceedings of the 2000 international symposium on Low power electronics and design
Battery capacity measurement and analysis using lithium coin cell battery
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Battery-driven dynamic power management of portable systems
ISSS '00 Proceedings of the 13th international symposium on System synthesis
Dynamic Voltage Scheduling Using Adaptive Filtering of Workload Traces
VLSID '01 Proceedings of the The 14th International Conference on VLSI Design (VLSID '01)
Battery-Driven System Design: A New Frontier in Low Power Design
ASP-DAC '02 Proceedings of the 2002 Asia and South Pacific Design Automation Conference
Design of a Wearable Sensor Badge for Smart Kindergarten
ISWC '02 Proceedings of the 6th IEEE International Symposium on Wearable Computers
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Improving trace cache hit rates using the sliding window fill mechanism and fill select table
MSP '04 Proceedings of the 2004 workshop on Memory system performance
Dynamic Power Management with Scheduled Switching Modes
Computer Communications
Information Sciences: an International Journal
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In this paper we introduce novel battery state aware strategies that improve the performance of battery operated systems. In our analysis, we consider the total amount of work done (or service) as the metric instead of considering just the lifetime. Based on our analysis using service curves, we formulate our static approach which generalizes many of the battery aware approaches introduced in the literatures. The results show that the static approach increases the battery utilization by 600% over a non battery aware approach. Furthermore, we show that our dynamic battery state aware approach improves upon the static approach by dynamically adapting the system performance level based on batteryes voltage slope. The results indicate that the dynamic approach achieves improvement of up to 20% over the static approach.