Energy budgeting for battery-powered sensors with a known task schedule
Proceedings of the 2006 IEEE/ACM international conference on Computer-aided design
Dynamic power management with hybrid power sources
Proceedings of the 44th annual Design Automation Conference
Energy management of DVS-DPM enabled embedded systems powered by fuel cell-battery hybrid source
ISLPED '07 Proceedings of the 2007 international symposium on Low power electronics and design
A fuel-cell-battery hybrid for portable embedded systems
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Adaptive Power Management Based on Reinforcement Learning for Embedded System
IEA/AIE '08 Proceedings of the 21st international conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems: New Frontiers in Applied Artificial Intelligence
Proceedings of the Conference on Design, Automation and Test in Europe
An adaptive hybrid dynamic power management algorithm for mobile devices
Computer Networks: The International Journal of Computer and Telecommunications Networking
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This paper addresses the problem of maximizing the capacity utilization of the battery power source in a portable electronic system under latency and loss rate constraints. First, a detailed stochastic model of a power-managed battery-powered electronic system is presented. The model, which is based on the theories of continuous-time Markovian decision processes (CTMDP) and stochastic networks, captures two important characteristics of today's rechargeable battery cells; i.e., the current rate-capacity characteristic and the relaxation induced capacity recovery. Next, the battery-aware dynamic power management (DPM) problem is formulated as a policy optimization problem and is solved by using a linear programming approach. Experimental results show that the proposed method outperforms existing methods by more than 20% in terms of battery service lifetime