Date : 2015. 01. 20 (Tue) 01:00 P.M.

Locate : EB5. 533

Presenter : Jemin Lee

Title: BatteryExtender: An Adaptive User-Guided Tool for Power Management of Mobile Devices

Authors    

Grace Metri   Department of Computer Science, Wayne State University

Abstract

The battery life of mobile devices is one of their most important resources. Much of the literature focuses on accurately profiling the power consumption of device components or enabling application developers to develop energy-efficient applications through fine-grained power profiling. However, there is a lack of tools to enable users to extend battery life on demand. What can users do if they need their device to last for a specific duration in order to perform a specific task? To this extent, we developed BatteryExtender, a user-guided power management tool that enables the reconfiguration of the device’s resources based on the workload quirement, similar to the principle of creating virtual machines in the cloud. It predicts the attery life savings based on the new configuration, in addition to predicting the impact of running applications
on the battery life. Through our experimental analysis, BatteryExtender decreased the energy consumption between 10.03% and 20.21%, and in rare cases by up to 72.83%. The accuracy rate ranged between 92.37% and 99.72%.

Proceeding UbiComp ’14,

Full Text: Paper 

Article source: //eslab.cnu.ac.kr/en/Mobile/18-BatteryExtender-An-Adaptive-User-Guided-Tool-for-Power-Management-of-Mobile-Devices.html