eGEN: an energy-saving modeling language and code generator for location-sensing of mobile apps

Kowndinya Boyalakuntla, Marimuthu Chinnakali, Sridhar Chimalakonda, K. Chandrasekaran

Abstract: Given the limited tool support for energy-saving strategies during the design phase of android applications, developing battery-aware, location-based android applications is a non-trivial task for developers. To this end, we propose eGEN, consisting of (1) a Domain-Specific Modeling Language (DSML) and (2) a code generator to specify and create native battery-aware, location-based mobile applications. We evaluated eGEN by instrumenting the generated battery-aware code in five location-based, open-source android applications and compared the energy consumption with non-eGEN versions. The experimental results show 188 mA (8.34% of battery per hour) of average reduction in battery consumption while showing only 97 meters of degradation in location accuracy over three kilometers of a cycling path. Hence, we see this tool as a first step in helping developers write battery-aware code in location-based android applications. The GitHub repository with source code and all artifacts is available at https://github.com/Kowndinya2000/egen, and the tool demo video at https://youtu.be/Iadfh4cCw8I.