IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v18y2022i5p15501477211049917.html
   My bibliography  Save this article

A distributed energy-efficient opportunistic routing accompanied by timeslot allocation in wireless sensor networks

Author

Listed:
  • Man Gun Ri
  • Ye Song Han
  • Jin Pak

Abstract

Sensed data can be forwarded only in one direction to the base station in one-dimensional queue wireless sensor networks different from mesh structure, so the network lifetime will be shortened if some continuous neighboring nodes have run out of their energy. So designing routing protocols for balancing energy consumption is a challenging problem. However, traditional and existing opportunistic routing protocols for one-dimensional queue wireless sensor network proposed so far have not yet addressed this problem to prolong the network lifetime by introducing sleep mode. In this article, we propose a distributed energy-efficient opportunistic routing algorithm accompanied by timeslot allocation by using specific network topology of one-dimensional queue wireless sensor network. In our new algorithm, clustering and routing tree construction is performed while introducing the optimal relay transmission distance achieved by using opportunistic routing principle, and at the same time, interference-free wake up time is scheduled, which may optimize energy consumption and decrease the number of various control messages as possible to prolong the network lifetime. Furthermore, this improves energy efficiency by introducing the operation mode giving up cluster head role. Simulation results show that the proposed protocol can significantly improve the network performance such as energy consumption and network connectivity, when compared with other existing protocols.

Suggested Citation

  • 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.
    • Handle: RePEc:sae:intdis:v:18:y:2022:i:5:p:15501477211049917
    DOI: 10.1177/15501477211049917
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/15501477211049917
    Download Restriction: no
    File URL: https://libkey.io/10.1177/15501477211049917?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. 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.
    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.

    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:sae:intdis:v:18:y:2022:i:5:p:15501477211049917. 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: SAGE Publications (email available below). General contact details of provider: .

    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.