Paper Info
Title
FEPMA: Fine-grained event-driven power meter for android smartphones based on device driver layer event monitoring
Abstract
This paper introduces a novel sensor-less, event-driven power analysis framework called FEPMA for providing highly accurate and nearly instantaneous estimates of power dissipation in an Android smartphone. The key idea is to collect and correctly record various events of interest within a smartphone as applications are running on the application processor within it. This is in turn done by instrumenting the Android operating system to provide information about power/performance state changes of various smartphone components at the lowest layer of the kernel to avoid time stamping delays and component state observability issues. This technique then enables one to perform fine-grained (in time and space) power metering in the smartphone. Experimental results show significant accuracy improvement compared to previous approaches and good fidelity with respect to actual current measurements. The estimation error of the proposed method is lower by a factor of two than the state-of-the-art method.
Year
DOI
Venue
2014
10.7873/DATE.2014.380
DATE
Keywords
Field
DocType
state-of-the-art method,device driver layer event,fepma,power dissipation,component state observability issues,event-driven power analysis framework,android smartphones,record various event,power meters,time stamping delays,android operating system,android smartphone,estimation error,application processor,power metering,device driver layer event monitoring,performance state change,component state observability issue,smart phones,fine-grained event-driven power meter,various smartphone component,global positioning system,kernel,estimation
Kernel (linear algebra),Event monitoring,Power analysis,Fidelity,Observability,Android (operating system),Computer science,Real-time computing,Electricity meter,Metering mode
Conference
ISSN
Citations 
PageRank 
1530-1591
8
0.57
References 
Authors
11
6
Name
Order
Citations
PageRank
Kitae Kim1338.53
Donghwa Shin239632.34
Qing Xie328720.06
Yanzhi Wang41082136.11
Massoud Pedram578011211.32
Naehyuck Chang61985185.85