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In the case of many consumer-electronics devices, especially mobile phones, battery ca-pacity is severely restricted due to constraints on size and weight of the device. This implies that energy effi-ciency of these devices is very important to their usabil-ity. Hence, optimal management of power consumption of these devices is critical.
The nature of mobile devices running on a finite power source and employing wireless communication interfaces, ensures that simulations of these devices, model energy consumption to some degree.
A user based profiling technique is presented in [5, 10]. Whilst a further analysis of general energy consumption in has shown that networking is the biggest cause of power consumption on a smart phone device, again fuelling the need for more comprehensive network modelling.
We can use an original battery or an external power supply to measure the power consumption. External power sensors are the gold standard for mobile device power analysis owing to their high precision and accuracy. These tools are the most accurate and serve as the ground truth-values for other software-based tools.
Whilst a further analysis of general energy consumption in has shown that networking is the biggest cause of power consumption on a smart phone device, again fuelling the need for more comprehensive network modelling. The authors in also present data which shows energy hungry tasks and activities.
Similarly, OSs and popular apps such as WhatsApp and Facebook also provide a dark mode to reduce the power consumption of the device. This confirms that big companies in the mobile device arena are also aware of the power consumption problem and are trying to reduce it as much as possible.
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