Smartphones have limited battery capacity, so efficient power management is required for high-performance applications and to increase usage time. In recent years, efficient power management of smartphones has become very important as the demand for power use of smartphones has grown due to deep learning, games, virtual reality, and augmented reality applications. Existing low-power techniques of smartphones focus only on lowering power consumption without considering actual power consumption based on utilization of the central processing unit (CPU) and graphics processing unit (GPU), which are major components of smartphones. In addition, they do not take into consideration the strict use of resources within the component and what instructions are being processed to operate them. In this paper, we propose a low-power technique that manages power by calculating the actual power consumption of smartphones at execution time and classifying the detailed resource operating states of CPUs and GPUs. The proposed technique was implemented by linking the kernel and native app on a Galaxy S7 smartphone equipped with Android. In experiments with 15 workloads, the proposed technique achieves an energy reduction of 18.11% compared to the low-power technique of the interactive governor built into the Galaxy S7 with a small FPS reduction of 3.12%.
Bibliographical noteFunding Information:
This work was supported by the Future Combat System Network Technology Research Center program of the Defense Acquisition Program Administration and Agency for Defense Development (UD190033ED).
© 2022 by the authors.
- low power
- power estimation
ASJC Scopus subject areas
- Control and Systems Engineering
- Signal Processing
- Hardware and Architecture
- Computer Networks and Communications
- Electrical and Electronic Engineering