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Optimal Sensor Association and Data Collection in Power Materials Warehouse Based on Internet of Things

Author

Listed:
  • Fangqiuzi He

    (School of Art and Design, Wuhan Polytechnic University, Wuhan 430074, China)

  • Junfeng Xu

    (Wuhan Maritime Communication Research Institute, Wuhan 430074, China)

  • Jinglin Zhong

    (Department of Mathematics, University of Calgary, Calgary, AB T2N 1V4, Canada)

  • Guang Chen

    (School of Mechanical Engineering and Electronic Information, China University of Geosciences, Wuhan 430074, China)

  • Shixin Peng

    (National Engineering Laboratory for Educational Big Data, Central China Normal University, Wuhan 430079, China)

Abstract

In order to realize the intelligent management of a power materials warehouse, the Internet of Things based on wireless sensor networks (WSNs) is a promising effective solution. Considering the limited battery capacity of sensor nodes, the optimization of the topology control and the determination of the amount of collected data are critical for prolonging the survival time of WSNs and increasing the satisfaction of the warehouse supplier. Therefore, in this paper, an optimization problem on sensor association and acquisition data satisfaction is proposed, and the subproblem of the sensor association is modeled as the knapsack problem. To cope with it, the block coordinate descent method is used to obtain the suboptimal solution. A sensor association scheme based on the ant colony algorithm (ACO) is proposed, and the upper and lower bounds of this optimization problem are also obtained. After this, a cluster head selection algorithm is given to find the optimal cluster head. Finally, the experimental simulations show that the algorithms proposed in this paper can effectively improve the energy utilization of WSNs to ensure the intelligent management of a power materials warehouse.

Suggested Citation

  • Fangqiuzi He & Junfeng Xu & Jinglin Zhong & Guang Chen & Shixin Peng, 2021. "Optimal Sensor Association and Data Collection in Power Materials Warehouse Based on Internet of Things," Energies, MDPI, vol. 14(21), pages 1-16, November.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7449-:d:674721
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    Cited by:

    1. Hao Wang & Quan Liu & Hongyang Zhang & Yinlong Jin & Wenzhen Yu, 2022. "A Two-Stage Decision-Making Method Based on WebGIS for Bulk Material Transportation of Hydropower Construction," Energies, MDPI, vol. 15(5), pages 1-21, February.

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