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Energy Efficient Cooperative Computation Algorithm in Energy Harvesting Internet of Things

Author

Listed:
  • Haneul Ko

    (Department of Computer Convergence Software, Korea University, Sejong 30019, Korea)

  • Jaewook Lee

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

  • Seokwon Jang

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

  • Joonwoo Kim

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

  • Sangheon Pack

    (School of Electrical Engineering, Korea University, Seoul 02841, Korea)

Abstract

The limited battery capacity of Internet of Things (IoT) devices is a major deployment barrier for IoT-based computing systems. In this paper, we propose an energy efficient cooperative computation algorithm (EE-CCA). In an EE-CCA, a pair of IoT devices decide whether to offload some parts of the task to the opponent by considering their energy levels and the task deadline. To minimize the energy outage probability while completing most of tasks before their deadlines, we formulate a constraint Markov decision process (CMDP) problem and the optimal offloading strategy is obtained by linear programming (LP). Meanwhile, an optimization problem of finding pairs of IoT devices (i.e., IoT device pairing problem) is formulated under the optimal offloading strategy. Evaluation results demonstrate that the EE-CCA can reduce the energy outage probability up to 78 % compared with the random offloading scheme while completing tasks before their deadlines with high probability.

Suggested Citation

  • Haneul Ko & Jaewook Lee & Seokwon Jang & Joonwoo Kim & Sangheon Pack, 2019. "Energy Efficient Cooperative Computation Algorithm in Energy Harvesting Internet of Things," Energies, MDPI, vol. 12(21), pages 1-19, October.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:21:p:4050-:d:279810
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    References listed on IDEAS

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    1. Yilun Shang, 2018. "Resilient Multiscale Coordination Control against Adversarial Nodes," Energies, MDPI, vol. 11(7), pages 1-17, July.
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    Cited by:

    1. Chung-Jen Chou & Shyh-Biau Jiang & Tse-Liang Yeh & Li-Duan Tsai & Ku-Yen Kang & Ching-Jung Liu, 2020. "A Portable Direct Methanol Fuel Cell Power Station for Long-Term Internet of Things Applications," Energies, MDPI, vol. 13(14), pages 1-13, July.
    2. Mahmoud Wagih & Abiodun Komolafe & Bahareh Zaghari, 2020. "Separation-Independent Wearable 6.78 MHz Near-Field Radiative Wireless Power Transfer using Electrically Small Embroidered Textile Coils," Energies, MDPI, vol. 13(3), pages 1-14, January.

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