DVFS energy-saving scheduling of navigation receiver based on equilibrium optimization

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Abstract

Hand-held or portable navigation receivers are powered by battery. The energy-saving design is very important to extend battery life. High-precision geodesic navigation receivers can be installed in fixed ground station. Dynamic-adaptive navigation receivers can be carried in a ship, aircraft, missile, or other vehicle. Although those carriers can supply sufficient power, low power design is of great benefit to system cooling, thus improves the receiver life cycle. Receiver processor can schedule task in busy or idle state. Dynamic Voltage and Frequency Scaling (DVFS) technology adjusts system voltage and frequency dynamically to make use of idle state, thus effectively saves system energy. This paper analyses the energy-saving scheduling design of multi-channel receivers, where the power consumption is remarkably reduced based on DVFS, meanwhile receiver works well in real-time. A DVFS energy-saving scheduling method based on equilibrium optimization is proposed, where the receiver clock frequency is dynamically adjusted corresponding to the number of satellites available using utilization equilibrium rule and its reverse counterpart. Our method optimizes the energy-saving factor based on utilization feedback approach and schedulability condition approach, and voltage and frequency adjusting is transformed into execution time increase. Monte Carlo simulations and experiment results show that our method is independent of scheduling algorithm and schedulability condition, and has low time complexity. Utilization equilibrium rule can obtain more balanced energy-saving factor compared with its reverse counterpart, and schedulability condition approach can acquire higher total utilization compared with utilization feedback approach, thus effectively reduce receiver power consumption. © 2013 Springer-Verlag Berlin Heidelberg.

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Wu, W., Ge, R., Ni, S. J., & Wang, F. X. (2013). DVFS energy-saving scheduling of navigation receiver based on equilibrium optimization. In Lecture Notes in Electrical Engineering (Vol. 243 LNEE, pp. 617–626). Springer Verlag. https://doi.org/10.1007/978-3-642-37398-5_57

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