Energy efficient adaptation engines for android applications
Context The energy consumption of mobile devices is increasing due to the improvement in
their components (eg, better processors, larger screens). Although the hardware consumes
the energy, the software is responsible for managing hardware resources such as the
camera software and its functionality, and therefore, affects the energy consumption. Energy
consumption not only depends on the installed code, but also on the execution context
(environment, devices status) and how the user interacts with the application. Objective In�…
their components (eg, better processors, larger screens). Although the hardware consumes
the energy, the software is responsible for managing hardware resources such as the
camera software and its functionality, and therefore, affects the energy consumption. Energy
consumption not only depends on the installed code, but also on the execution context
(environment, devices status) and how the user interacts with the application. Objective In�…
Abstract
Context The energy consumption of mobile devices is increasing due to the improvement in their components (e.g., better processors, larger screens). Although the hardware consumes the energy, the software is responsible for managing hardware resources such as the camera software and its functionality, and therefore, affects the energy consumption. Energy consumption not only depends on the installed code, but also on the execution context (environment, devices status) and how the user interacts with the application.
Objective In order to reduce the energy consumption based on user behavior, it is necessary to dynamically adapt the application. However, the adaptation mechanism also consumes a certain amount of energy in itself, which may lead to an important increase in the energy expenditure of the application in comparison with the benefits of the adaptation. Therefore, this footprint must be measured and compared with the benefit obtained.
Method In this paper, we (1) determine the benefits, in terms of energy consumption, of dynamically adapting mobile applications, based on user behavior; and (2) advocate the most energy-efficient adaptation mechanism. We provide four different implementations of a proposed adaptation model and measure their energy consumption.
Results The proposed adaptation engines do not increase the energy consumption when compared to the benefits of the adaptation, which can reduce the energy consumption by up to 20%.
Conclusion The adaptation engines proposed in this paper can decrease the energy consumption of the mobile devices based on user behavior. The overhead introduced by the adaptation engines is negligible in comparison with the benefits obtained by the adaptation.
Elsevier
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