energy-aware complexity adaptation for mobile video calls
High energy consumption has become a challenge for multimedia applications on mobile platforms. We propose a cross layer framework that integrates complexity adaptation and energy conservation for mobile video calls. First we select the most utility-aware encoding and decoding parameters for videos of different motion levels through extensive offline profiling and analysis. Then we design a feedback algorithm to adaptively apply different coding parameters while monitoring the system performance online during a video call. To minimize energy consumption, we utilize Dynamic Voltage and Frequency Scaling (DVFS) for the CPU and buffered transmissions for the network. Our experimental results show an effective saving on energy consumption, with on average 52\% savings on the CPU and 30\% on the wireless network, while still maintaining high quality service.
adaptation mobile video calls energy-use optimization