Battery Voltage Discharge Rate Prediction and Video Content Adaptation in Mobile Devices on 3G Access Networks

[Abstract] According to Cisco, mobile multimedia services now account for more than half the total amount of Internet traffic. This trend is burdening mobile devices in terms of power consumption, and as a result, more effort is needed to devise a range of power-saving techniques. While most power-saving techniques are based on sleep scheduling of network interfaces, little has been done to devise multimedia content adaptation techniques. In this paper, we propose a multiple linear regression model that predicts the battery voltage discharge rate for several video send bit rates in a VoIP application. The battery voltage discharge rate needs to be accurately estimated in order to estimate battery life in critical VoIP contexts, such as emergency communication. In our proposed model, the range of video send bitrates is carefully chosen in order to maintain an acceptable VoIP quality of experience. From extensive profiling, the empirical results show that the model effectively saves power and prolongs real-time VoIP sessions when deployed in power-driven adaptation schemes.

[Keywords] QoE; power; mobile devices; quality adaptation; discharge rate