IDEAS home Printed from https://ideas.repec.org/a/hin/complx/5781620.html
   My bibliography  Save this article

Path Optimization of Mobile Sink Node in Wireless Sensor Network Water Monitoring System

Author

Listed:
  • Fan Chao
  • Zhiqin He
  • Aiping Pang
  • Hongbo Zhou
  • Junjie Ge

Abstract

In the water area monitoring of the traditional wireless sensor networks (WSNs), the monitoring data are mostly transmitted to the base station through multihop. However, there are many problems in multihop transmission in traditional wireless sensor networks, such as energy hole, uneven energy consumption, unreliable data transmission, and so on. Based on the high maneuverability of unmanned aerial vehicles (UAVs), a mobile data collection scheme is proposed, which uses UAV as a mobile sink node in WSN water monitoring and transmits data wirelessly to collect monitoring node data efficiently and flexibly. In order to further reduce the energy consumption of UAV, the terminal nodes are grouped according to the dynamic clustering algorithm and the nodes with high residual energy in the cluster are selected as cluster head nodes. Then, according to the characteristics of sensor nodes with a certain range of wireless signal coverage, the angular bisection method is introduced on the basis of the traditional ant colony algorithm to plan the path of UAV, which further shortens the length of the mobile path. Finally, the effectiveness and correctness of the method are proved by simulation and experimental tests.

Suggested Citation

  • Fan Chao & Zhiqin He & Aiping Pang & Hongbo Zhou & Junjie Ge, 2019. "Path Optimization of Mobile Sink Node in Wireless Sensor Network Water Monitoring System," Complexity, Hindawi, vol. 2019, pages 1-10, November.
    • Handle: RePEc:hin:complx:5781620
    DOI: 10.1155/2019/5781620
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2019/5781620.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2019/5781620.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2019/5781620?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Jin Wang & Yu Gao & Wei Liu & Arun Kumar Sangaiah & Hye-Jin Kim, 2019. "An intelligent data gathering schema with data fusion supported for mobile sink in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 15(3), pages 15501477198, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Rahmad Syah & Safoura Faghri & Mahyuddin KM Nasution & Afshin Davarpanah & Marek Jaszczur, 2021. "Modeling and Optimization of Wind Turbines in Wind Farms for Solving Multi-Objective Reactive Power Dispatch Using a New Hybrid Scheme," Energies, MDPI, vol. 14(18), pages 1-22, September.
    2. Chang Zhou & Zhenghong Gu & Yu Gao & Jin Wang, 2019. "An Improved Style Transfer Algorithm Using Feedforward Neural Network for Real-Time Image Conversion," Sustainability, MDPI, vol. 11(20), pages 1-15, October.
    3. Man Gun Ri & Ye Song Han & Jin Pak, 2022. "A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks," International Journal of Distributed Sensor Networks, , vol. 18(5), pages 15501477211, May.
    4. Ai-Qing Tian & Shu-Chuan Chu & Jeng-Shyang Pan & Huanqing Cui & Wei-Min Zheng, 2020. "A Compact Pigeon-Inspired Optimization for Maximum Short-Term Generation Mode in Cascade Hydroelectric Power Station," Sustainability, MDPI, vol. 12(3), pages 1-19, January.
    5. Zi-Xuan Yu & Meng-Shi Li & Yi-Peng Xu & Sheraz Aslam & Yuan-Kang Li, 2021. "Techno-Economic Planning and Operation of the Microgrid Considering Real-Time Pricing Demand Response Program," Energies, MDPI, vol. 14(15), pages 1-28, July.
    6. Ali Toolabi Moghadam & Bahram Bahramian & Farid Shahbaazy & Ali Paeizi & Tomonobu Senjyu, 2023. "Stochastic Flexible Power System Expansion Planning, Based on the Demand Response Considering Consumption and Generation Uncertainties," Sustainability, MDPI, vol. 15(2), pages 1-19, January.
    7. Joanna Piotrowska-Woroniak & Tomasz Szul & Krzysztof Cieśliński & Jozef Krilek, 2022. "The Impact of Weather-Forecast-Based Regulation on Energy Savings for Heating in Multi-Family Buildings," Energies, MDPI, vol. 15(19), pages 1-30, October.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:5781620. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.