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Reinforcement Learning-Based Dynamic Power Management for Energy Harvesting Wireless Sensor Network

  • Conference paper
Next-Generation Applied Intelligence (IEA/AIE 2009)

Abstract

In this study, a dynamic power management method based on reinforcement learning is proposed to improve the energy utilization for energy harvesting wireless sensor networks. Simulations of the proposed method on wireless sensor nodes powered by solar power are performed. Experimental results demonstrate that the proposed method outperforms the other power management method in achieving longer sustainable operations for energy harvesting wireless sensor network.

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© 2009 Springer-Verlag Berlin Heidelberg

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Chaoming Hsu, R., Liu, CT., Lee, WM. (2009). Reinforcement Learning-Based Dynamic Power Management for Energy Harvesting Wireless Sensor Network. In: Chien, BC., Hong, TP., Chen, SM., Ali, M. (eds) Next-Generation Applied Intelligence. IEA/AIE 2009. Lecture Notes in Computer Science(), vol 5579. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02568-6_41

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  • DOI: https://doi.org/10.1007/978-3-642-02568-6_41

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-02567-9

  • Online ISBN: 978-3-642-02568-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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