Excessive power consumption and high temperatures are some of the key factors limiting battery charge life and performance of current mobile devices or smartphones. Existing power management solutions do not account for user-experience, which can impact user satisfaction. In this paper we propose a joint power and thermal management solution, which takes a proactive approach in reducing energy consumption while providing expected user-experience. The proposed technique modulates the operating conditions based on users application preferences and exploits the "change blindness" effect to reduce display power consumption. Another important aspect of our implementation is that it does not require any restructuring of the underlying operating system. A novel thermal model of the entire smartphone was built with the purpose of monitoring and controlling the operating conditions to keep the device temperatures within safe operating ranges. Our ready-to-use management technique has been implemented on Google Nexus 5 and has been demonstrated to achieve a 46% application-specific savings on power consumption and up to 35% savings in power consumption at the device level. The mean temperature estimation error is 1.17 • C.

Mobile devices today contain many power hungry subsystems and execute different applications. Standard power management is not aware of the desired battery lifetime and has no visibility into which applications are executing. However, power consumption is strongly dependent on which applications are executed. In this work, we propose a novel power characterization strategy for mobile devices called application-dependent power states (AP-states). Based on that, we formulate a management problem to improve performance under battery lifetime constraints, and we implement the management framework on a real Android device. We call our framework BLAST: Battery Lifetime-constrained Adaptation with Selected Target. The goal of such framework is to maximize performance while letting the device battery to last at least for a certain required lifetime, and only requires the user to select the desired target lifetime. The implementation does not require OS modifications and can be ported and installed to any Android device. We experimentally verify that our strategy can still meets user experience requirements with a selected target battery lifetime extension of at least 25%.

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