Research Article
Kraken.me Mobile: The Energy Footprint of Mobile Tracking
@INPROCEEDINGS{10.4108/icst.mobicase.2014.257823, author={Immanuel Schweizer and Roman B\aa{}rtl and Benedikt Schmidt and Fabian Kaup and Max M\'{y}hlh\aa{}user}, title={Kraken.me Mobile: The Energy Footprint of Mobile Tracking}, proceedings={6th International Conference on Mobile Computing, Applications and Services}, publisher={IEEE}, proceedings_a={MOBICASE}, year={2014}, month={11}, keywords={power consumption mobile tracking soft sensors}, doi={10.4108/icst.mobicase.2014.257823} }- Immanuel Schweizer
Roman Bärtl
Benedikt Schmidt
Fabian Kaup
Max Mühlhäuser
Year: 2014
Kraken.me Mobile: The Energy Footprint of Mobile Tracking
MOBICASE
IEEE
DOI: 10.4108/icst.mobicase.2014.257823
Abstract
Power consumption can make or break the success of mobile applications. This is especially true for applications requiring constant access to sensor readings as sensors tend to consume considerable amounts of energy. A lot of attention has been focused on reducing power consumption for hardware sensors both from a hardware and software perspective. However, mobile phones enable applications to also gather software artifacts employing so called soft sensors, e.g., calendar, contacts, browsing history, etc.
Soft sensors are especially important when considering personal assistant systems, life logs etc. They provide additional deep insight into human behavior patterns and user goals. Unfortunately, most tracking application do not consider these soft sensors and their power consumption is mostly unknown.
In this paper we introduce the Kraken.me mobile tracking application. It is part of the Kraken.me framework, tracking mobile, desktop, and social interactions. The application tracks both hard and soft sensors to enable the creation of rich user profiles. Our main contribution is a thorough evaluation of the power consumption of each individual sensor used and the combination in the Kraken.me application. Using a high-accuracy measurement setup, we provide an in-depth power analysis of both soft and hard sensors. We believe these insights can help researchers and developers of mobile tracking applications to design more power efficient and, thus, more successful tools.
