PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency

Muhammad Hanif Jofri (1), Muharman Lubis (2), Mohd Farhan Md Fudzee (3), Shahreen Kasim (4), Mohd Norasri Ismail (5), Deden Witarsyah (6)
(1) Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Johor, Malaysia
(2) School of Industrial Engineering, Telkom University, Jalan Telekomunikasi No. 1, Bandung, 40257, Indonesia
(3) Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Johor, Malaysia
(4) Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Johor, Malaysia
(5) Faculty of Computer Science and Information Technology, Universiti Tun Hussein Onn Malaysia, 86400, Johor, Malaysia
(6) Department of Information System, Faculty of Industrial Engineering, Telkom University, Bandung, 40257, Indonesia
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How to cite (IJASEIT) :
Jofri, Muhammad Hanif, et al. “PowerDoW (Power Digital Offset Weightage): Video Content-Adaptation (VCA) Profiling in Smartphone Devices for Energy Efficiency”. International Journal on Advanced Science, Engineering and Information Technology, vol. 10, no. 6, Dec. 2020, pp. 2491-7, doi:10.18517/ijaseit.10.6.10881.
Nowadays, the rapid enhancement of Internet connectivity and the recent progression of smartphone technologies lead to better smartphones quality towards video streaming activity. With the massive production of smartphone devices today, motivate studies of energy consumption behaviors to extend the smartphone device battery-life. Therefore, existing designs for smartphone devices occasionally lack energy-aware thus it need profiling optimization technique that reduces energy usage. Energy profiling in smartphone devices is one of the practical criteria for saving energy in smartphone devices during video streaming session. Energy efficiency features for smartphone devices, profiling and video content adaptation approach are the most critical parts for the energy-efficient while streaming in course. However, the consideration of energy-aware profiling area has not yet been discovered widely. In this case, appointing promising approaches will be used to reduce energy consumption in the smartphone devices during video streaming session. A framework called PowerDoW will be benefited towards adding energy adaptation strategies. PowerDoW framework manage and utilize system profiling status to attain the entire streaming session activity and classify the streaming video format depending on the selective video parameter. Selection of the best quality depending on low energy usage will be determined in the profiling experimentation. The experimentations are based on the Android operating system in smartphone devices—instrumentation setup testing by using PowerTutor application to measure energy consumption in real-time. The result indicates that PowerDoW framework can reduce a huge energy consumption by selecting suitable video content adaptation during video streaming session.

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