Dynamic power optimization targeting user delays in interactive systems

Power has become a major concern for mobile computing systems such as laptops and handhelds, on which a significant fraction of software usage is interactive instead of compute-intensive. For interactive systems, an analysis shows that more than 90 percent of system energy and time is spent waiting for user input. Such idle periods provide vast opportunities for dynamic power management (DPM) and voltage scaling (DVS) techniques to reduce system energy. In this work, we propose to utilize user interface information to predict user delays based on human-computer interaction history and theories from the field of psychology. We show that such a delay prediction can be combined with DPM/DVS for aggressive power optimization. We verify the effectiveness of our methodologies with usage traces collected on a personal digital assistant (PDA) and a system power model based on accurate measurements. Experiments show that using predicted user delays for DPM/DVS achieves an average of 21.9 percent system energy reduction with little sacrifice in user productivity or satisfaction.