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On Hybrid Energy Utilization in Wireless Sensor Networks

Author

Listed:
  • Mohammad Tala’t

    (Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu 30012, Taiwan
    These authors are the members of IEEE.)

  • Chih-Min Yu

    (Department of Electronics Engineering, Chung Hua University, Hsinchu 30012, Taiwan
    These authors are the members of IEEE.)

  • Meng-Lin Ku

    (Department of Communication Engineering, National Central University, Taoyuan 32001, Taiwan
    These authors are the members of IEEE.)

  • Kai-Ten Feng

    (Department of Electrical and Computer Engineering, National Chiao Tung University, Hsinchu 30012, Taiwan
    This author is the senior member of IEEE.)

Abstract

In a wireless sensor network (WSN), many applications have limited energy resources for data transmission. In order to accomplish a better green communication for WSN, a hybrid energy scheme can supply a more reliable energy source. In this article, hybrid energy utilization—which consists of constant energy source and solar harvested energy—is considered for WSN. To minimize constant energy usage from the hybrid source, a Markov decision process (MDP) is designed to find the optimal transmission policy. With a finite packet buffer and a finite battery size, an MDP model is presented to define the states, actions, state transition probabilities, and the cost function including the cost values for all actions. A weighted sum of constant energy source consumption and a packet dropping probability (PDP) are adopted as the cost value, enabling us to find the optimal solution for balancing the minimization of the constant energy source utilization and the PDP using a value iteration algorithm. As shown in the simulation results, the performance of optimal solution using MDP achieves a significant improvement compared to solution without its use.

Suggested Citation

  • Mohammad Tala’t & Chih-Min Yu & Meng-Lin Ku & Kai-Ten Feng, 2017. "On Hybrid Energy Utilization in Wireless Sensor Networks," Energies, MDPI, vol. 10(12), pages 1-11, November.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:1940-:d:120016
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    Citations

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    Cited by:

    1. Meihua Wang & Wei-Chang Yeh & Ta-Chung Chu & Xianyong Zhang & Chia-Ling Huang & Jun Yang, 2018. "Solving Multi-Objective Fuzzy Optimization in Wireless Smart Sensor Networks under Uncertainty Using a Hybrid of IFR and SSO Algorithm," Energies, MDPI, vol. 11(9), pages 1-23, September.
    2. Paweł Dymora & Mirosław Mazurek & Krzysztof Smalara, 2021. "Modeling and Fault Tolerance Analysis of ZigBee Protocol in IoT Networks," Energies, MDPI, vol. 14(24), pages 1-21, December.

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