Energy estimation tools for the Palm
Proceedings of the 3rd ACM international workshop on Modeling, analysis and simulation of wireless and mobile systems
PowerScope: A Tool for Profiling the Energy Usage of Mobile Applications
WMCSA '99 Proceedings of the Second IEEE Workshop on Mobile Computer Systems and Applications
Proceedings of the 42nd Annual IEEE/ACM International Symposium on Microarchitecture
An analysis of power consumption in a smartphone
USENIXATC'10 Proceedings of the 2010 USENIX conference on USENIX annual technical conference
CODES/ISSS '10 Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Fine-grained power modeling for smartphones using system call tracing
Proceedings of the sixth conference on Computer systems
Chameleon: a color-adaptive web browser for mobile OLED displays
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
Self-constructive high-rate system energy modeling for battery-powered mobile systems
MobiSys '11 Proceedings of the 9th international conference on Mobile systems, applications, and services
USENIX ATC'12 Proceedings of the 2012 USENIX conference on Annual Technical Conference
Empowering developers to estimate app energy consumption
Proceedings of the 18th annual international conference on Mobile computing and networking
DevScope: a nonintrusive and online power analysis tool for smartphone hardware components
Proceedings of the eighth IEEE/ACM/IFIP international conference on Hardware/software codesign and system synthesis
Towards better CPU power management on multicore smartphones
Proceedings of the Workshop on Power-Aware Computing and Systems
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System power models are important for power management and optimization on smartphones. However, existing approaches for power modeling have several limitations. Some require external power meters, which is not convenient for people to use. Other approaches either rely on the battery current sensing capability, which is not available on many smartphones, or take a long time to generate the power model. To overcome these limitations, we propose a new way of generating power models from battery voltage dynamics, called V-edge. V-edge is self-constructive and does not require current-sensing. Most importantly, it is fast in model building. Our implementation supports both component level power models and per-application energy accounting. Evaluation results using various benchmarks and applications show that the V-edge approach achieves high power modeling accuracy, and is two orders of magnitude faster than existing self-modeling approaches requiring no current-sensing.