Method to Derive Energy Profiles for Android Platform

Masterarbeit in der Abteilung Softwaretechnik


To improve quality of mobile applications on Android platform in sense of energy-efficiency, the programmers need appropriate tools. One of the method to estimate energy consumption of mobile applications is Energy Profiling (for example, using reference implementation - Android Power Profiles). This method allows to estimate energy consumption online, i.e. without using any external devices, while using reference data obtained via prior using of offline measurements tools.

The first-class entity of this method is Energy Profile of target device that contains information about distinct energy consumption of each component. There are at least two reasons why it is may be needed to derive Energy Profiles for specific Android device. First is inappropriate quality of built-in Android Power Profile for most of the devices presented on market. The significant improvement may be achieved even using reference power model developed for Android Power Profiles while using updated (i.e. derived for concrete target device) Power Profile. The second reason is using non-reference power models. Of course many engineers may consider using of specific power models that are suitable for Energy Profiling of very specific applications. In this case, the will need to have a method to obtain Energy Profile for this private power model.


This thesis describes the method of deriving various Energy Profiles for Android mobile devices. The following points are considered in this thesis: choosing appropriate hardware and architecture of software needed to automate the process of deriving Energy Profiles for Android mobile devices. The method was evaluated using test Android device and satisfactory improvement of estimation of energy consumption using reference power model (Android Power Profiles) was observed.

Prof. Dr. Andreas Winter (

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Software Engineering for Energy Efficiency

Energy Efficiency has become more important in recent years. This is shown by the development of engery consumption of information and communication technology (10 % of the german energy consumption in 2007). Futhermore battery development cannot keep up with the ubiquitous and powerful mobile devices. Research on hardware and low level software optimizations has been comprehensively explored. But the research on optimizing energy consumption on application level is still in its infancy. So in this project should be improved Energy Efficiency of applications by using reengineering services, like static and dynamic program analysis, and systematic code transformations.


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