Numerical recipes in C (2nd ed.): the art of scientific computing
Numerical recipes in C (2nd ed.): the art of scientific computing
A discrete-time battery model for high-level power estimation
DATE '00 Proceedings of the conference on Design, automation and test in Europe
Time-to-failure estimation for batteries in portable electronic systems
ISLPED '01 Proceedings of the 2001 international symposium on Low power electronics and design
Battery lifetime prediction for energy-aware computing
Proceedings of the 2002 international symposium on Low power electronics and design
Battery Life Estimation of Mobile Embedded Systems
VLSID '01 Proceedings of the The 14th International Conference on VLSI Design (VLSID '01)
MiBench: A free, commercially representative embedded benchmark suite
WWC '01 Proceedings of the Workload Characterization, 2001. WWC-4. 2001 IEEE International Workshop
Application-level prediction of battery dissipation
Proceedings of the 2004 international symposium on Low power electronics and design
IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems
Achieving viewing time scalability in mobile video streaming using scalable video coding
MMSys '10 Proceedings of the first annual ACM SIGMM conference on Multimedia systems
A system context-aware approach for battery lifetime prediction in smart phones
Proceedings of the 2011 ACM Symposium on Applied Computing
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This paper presents a novel, history-based, statistical technique for online battery lifetime prediction. The approach first takes a one-time, full cycle, voltage measurement of a constant load, and uses it to transform the partial voltage curve of the current workload into a form with robust predictability. Based on the transformed history curve, we apply a statistical method to make a lifetime prediction. We investigate the performance of the implementation of our approach on a widely used mobile device (HP iPAQ) running Linux, and compare it to two similar battery prediction technologies: ACPI and Smart Battery. We employ twenty-two constant and variable workloads to verify the efficacy of our approach. Our results show that this approach is efficient, accurate, and able to adapt to different systems and batteries easily.