Abstract
The optimization of the energy consumption in mobile devices can be performed on hardware and software components. For example, reducing the screen brightness or switching off GPS. The energy control must take into account both the current context and user habits, on the base of usage knowledge acquired from sensors and OS data records. The whole process of energy management then includes data collection, usage learning and analysis, decision-making and control of device components. To integrate these activities, we propose to use a software agent whose goal is to save the energy of the mobile device with the lowest effect on QoS.
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Acknowledgment
The authors would like to thank Intel Corporation and especially the Intel Research Council for the support given to this project.
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Chaib Draa, I., Grislin-Le Strugeon, E., Niar, S. (2017). An Energy-Aware Learning Agent for Power Management in Mobile Devices. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10350. Springer, Cham. https://doi.org/10.1007/978-3-319-60042-0_28
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DOI: https://doi.org/10.1007/978-3-319-60042-0_28
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