TY - GEN
T1 - Online estimation of the remaining energy capacity in mobile systems considering system-wide power consumption and battery characteristics
AU - Shin, Donghwa
AU - Kim, Kitae
AU - Chang, Naehyuck
AU - Lee, Woojoo
AU - Wang, Yanzhi
AU - Xie, Qing
AU - Pedram, Massoud
PY - 2013
Y1 - 2013
N2 - Emerging mobile systems integrate a lot of functionality into a small form factor with a small energy source in the form of rechargeable battery. This situation necessitates accurate estimation of the remaining energy in the battery such that user applications can be judicious on how they consume this scarce and precious resource. This paper thus focuses on estimating the remaining battery energy in Android OS-based mobile systems. This paper proposes to instrument the Android kernel in order to collect and report accurate subsystem activity values based on real-time profiling of the running applications. The activity information along with offline-constructed, regression-based power macro models for major subsystems in the smartphone yield the power dissipation estimate for the whole system. Next, while accounting for the rate-capacity effect in batteries, the total power dissipation data is translated into the battery's energy depletion rate, and subsequently, used to compute the battery's remaining lifetime based on its current state of charge information. Finally, this paper describes a novel application design framework, which considers the batterys state-of-charge (SOC), batterys energy depletion rate, and service quality of the target application. The benefits of the design framework are illustrated by examining an archetypical case, involving the design space exploration and optimization of a GPS-based application in an Android OS.
AB - Emerging mobile systems integrate a lot of functionality into a small form factor with a small energy source in the form of rechargeable battery. This situation necessitates accurate estimation of the remaining energy in the battery such that user applications can be judicious on how they consume this scarce and precious resource. This paper thus focuses on estimating the remaining battery energy in Android OS-based mobile systems. This paper proposes to instrument the Android kernel in order to collect and report accurate subsystem activity values based on real-time profiling of the running applications. The activity information along with offline-constructed, regression-based power macro models for major subsystems in the smartphone yield the power dissipation estimate for the whole system. Next, while accounting for the rate-capacity effect in batteries, the total power dissipation data is translated into the battery's energy depletion rate, and subsequently, used to compute the battery's remaining lifetime based on its current state of charge information. Finally, this paper describes a novel application design framework, which considers the batterys state-of-charge (SOC), batterys energy depletion rate, and service quality of the target application. The benefits of the design framework are illustrated by examining an archetypical case, involving the design space exploration and optimization of a GPS-based application in an Android OS.
UR - http://www.scopus.com/inward/record.url?scp=84877772175&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84877772175&partnerID=8YFLogxK
U2 - 10.1109/ASPDAC.2013.6509559
DO - 10.1109/ASPDAC.2013.6509559
M3 - Conference contribution
AN - SCOPUS:84877772175
SN - 9781467330299
T3 - Proceedings of the Asia and South Pacific Design Automation Conference, ASP-DAC
SP - 59
EP - 64
BT - 2013 18th Asia and South Pacific Design Automation Conference, ASP-DAC 2013
T2 - 2013 18th Asia and South Pacific Design Automation Conference, ASP-DAC 2013
Y2 - 22 January 2013 through 25 January 2013
ER -