IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v14y2018i8p1550147718794617.html
   My bibliography  Save this article

A hierarchical adaptive routing algorithm of wireless sensor network based on software-defined network

Author

Listed:
  • Zhong-Nan Zhao
  • Jian Wang
  • Hong-Wei Guo

Abstract

The target tracking issue has always been the hotspot in wireless sensor network, and with the emergence of new application in multimedia and real-time transmission, new requirements are proposed for transmission performance of target tracking routing; therefore, a software-defined network–based hierarchical adaptive routing algorithm of wireless sensor network is proposed in this article. The algorithm takes into account both network energy and throughput, uses Hopfield neural network algorithm to calculate the optimal path among adjacent clusters as a local routing (LR), and builds the Multi-choice Knapsack Problem model based on local paths to realize end-to-end global routing, in order to realize the routing of tracking target information under multi-objective conditions. The test bed includes physical and simulation tests. Experimental results show that the proposed algorithm is superior to low energy adaptive clustering hierarchy (LEACH) and Sequential Assignment Routing under different test scenarios.

Suggested Citation

  • Zhong-Nan Zhao & Jian Wang & Hong-Wei Guo, 2018. "A hierarchical adaptive routing algorithm of wireless sensor network based on software-defined network," International Journal of Distributed Sensor Networks, , vol. 14(8), pages 15501477187, August.
  • Handle: RePEc:sae:intdis:v:14:y:2018:i:8:p:1550147718794617
    DOI: 10.1177/1550147718794617
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147718794617
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147718794617?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. Lersteau, Charly & Rossi, André & Sevaux, Marc, 2016. "Robust scheduling of wireless sensor networks for target tracking under uncertainty," European Journal of Operational Research, Elsevier, vol. 252(2), pages 407-417.
    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. Keskin, Muhammed Emre, 2017. "A column generation heuristic for optimal wireless sensor network design with mobile sinks," European Journal of Operational Research, Elsevier, vol. 260(1), pages 291-304.
    2. Mac Cawley, Alejandro & Maturana, Sergio & Pascual, Rodrigo & Tortorella, Guilherme Luz, 2022. "Scheduling wine bottling operations with multiple lines and sequence-dependent set-up times: Robust formulation and a decomposition solution approach," European Journal of Operational Research, Elsevier, vol. 303(2), pages 819-839.
    3. Chen, Yi-Ting & Sun, Edward W. & Chang, Ming-Feng & Lin, Yi-Bing, 2021. "Pragmatic real-time logistics management with traffic IoT infrastructure: Big data predictive analytics of freight travel time for Logistics 4.0," International Journal of Production Economics, Elsevier, vol. 238(C).
    4. Seddik, Yasmina & Hanzálek, Zdenek, 2017. "Match-up scheduling of mixed-criticality jobs: Maximizing the probability of jobs execution," European Journal of Operational Research, Elsevier, vol. 262(1), pages 46-59.
    5. Lersteau, Charly & Rossi, André & Sevaux, Marc, 2018. "Minimum energy target tracking with coverage guarantee in wireless sensor networks," European Journal of Operational Research, Elsevier, vol. 265(3), pages 882-894.

    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:14:y:2018:i:8:p:1550147718794617. 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.