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In this paper we use a large dataset of wireless user activity traces to test the various dynamic power management schemes. We also present and test our own empirically-driven dynamic power-saving algorithms, which are based on prior observations of user activity patterns. We believe that this sort of analysis can guide adoption of a user-behavior driven approach to radio and communications power management, and, in networking-centric devices, power management for the entire device. Additionally, understanding the characteristics of user-activity and efficient mechanisms to predict this activity can help inform the design of power-saving schemes for future networking protocols.
Phillips et al. (Tue,) studied this question.