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|Title:||In-vivo and offline optimisation of energy use in the presence of small energy signals: case study on a popular Android library|
|Citation:||MobiQuitous '18 Proceedings of the 15th EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services, 2018 / Schulzrinne, H., Li, P. (ed./s), pp.207-215|
|Publisher:||Association for Computing Machinery|
|Series/Report no.:||ACM International Conference Proceeding Series|
|Conference Name:||EAI International Conference on Mobile and Ubiquitous Systems: Computing, Networking and Services (Mobiquitous) (5 Nov 2018 - 7 Nov 2018 : New York City, NY)|
|Mahmoud A. Bokhari, Brad Alexander, Markus Wagner|
|Abstract:||Energy demands of applications on mobile platforms are increasing. As a result, there has been a growing interest in optimising their energy efficiency. As mobile platforms are fast-changing, diverse and complex, the optimisation of energy use is a non-trivial task. To date, most energy optimisation methods either use models or external meters to estimate energy use. Unfortunately, it becomes hard to build widely applicable energy models, and external meters are neither cheap nor easy to set up. To address this issue, we run application variants in-vivo on the phone and use a precise internal battery monitor to measure energy use. We describe a methodology for optimising a target application in-vivo and with application-specific models derived from the device's own internal meter based on jiffies and lines of code. We demonstrate that this process produces a significant improvement in energy efficiency with limited loss of accuracy.|
|Rights:||© 2018 Copyright held by the owner/author(s). Publication rights licensed to ACM.|
|Appears in Collections:||Aurora harvest 8|
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