| Summary: | 碩士 === 國立清華大學 === 資訊工程學系 === 100 === Energy optimization has been a popular area of research in mobile computing device. However, most of the previous researches on energy optimization focus on the device itself and seldom consider the interaction of the user and the device, or take the user behavior pattern as well as user experience into account. One area where energy optimization can be exercised on mobile device is background applications. Applications running in background will consume energy, leading to shorter usage time and worse user experience. However, if we kill every application whenever it is put into background, the relaunch time will be very long once the user wants to switch back to that application. This also leads to bad user experience.
Apparently, we need a good mechanism that keeps only those background applications that will be needed by user. This requires that user behavior in the next period time be modeled and predicted accurately. We believe accurate prediction can be made depends on the behavior patterns of the usage of the apps and other observable context variables.
In this thesis, we introduce such a mechanism that manages background application for energy optimization by predicting user behavior through usage modeling.
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