Analysis of characteristics of power consumption for context-aware mobile applications

Abstract

In recent years, a large portion of smartphone applications (Apps) has targeted context-aware services. They aim to perceive users' real-time context like his/her location, actions, or even emotion, and to provide various customized services based on the inferred context. However, context-awareness in mobile environments has some challenging issues due to limitations of devices themselves. Limited power is regarded as the most critical problem in context-awareness on smartphones. Many studies have tried to develop low-power methods, but most of them have focused on the power consumption of H/W modules of smartphones such as CPU and LCD. Only a few research papers have recently started to present some S/W-based approaches to improve the power consumption. That is, previous works did not consider energy consumed by context-awareness of Apps. Therefore, in this paper, we focus on the power consumption of context-aware Apps. We analyze the characteristics of context-aware Apps in a perspective of the power consumption, and then define two main factors which significantly influence the power consumption: a sort of context that context-aware Apps require for their services and a type of ways that a user uses them. The experimental result shows the reasonability and the possibility to develop low-power methods based on our analysis. That is, our analysis presented in this paper will be a foundation for energy-efficient context-aware services in mobile environments.