IDEAS home Printed from https://ideas.repec.org/a/sae/intdis/v13y2017i11p1550147717744993.html

Deployment optimization for a long-distance wireless backhaul network in industrial cyber physical systems

Author

Listed:
  • Jintao Wang
  • Xi Jin
  • Peng Zeng
  • Ming Wan
  • Changqing Xia

Abstract

Industrial wireless networks are an important component of industrial cyber physical systems, and their transmission performance directly determines the quality of the entire system. During deployment, the nodes of an industrial wireless network can be deployed in only some specific regions due to physical environment restrictions in the factory; thus, occlusions are not always effectively circumvented and network performance is reduced. Therefore, this article focuses on the layout problem of the industrial backhaul network: a WiFi long-distance, multi-hop network. The optimization objectives were network throughput and construction cost, and the network delay was used as a constraint. For small networks, we propose a hierarchical traversal method to obtain the optimal solution, whereas for a large network, we used a hierarchical heuristic method to obtain an approximate solution, and for extremely large networks, we used a parallel interactive local search algorithm based on dynamic programming. Then, if the original network layout cannot meet the transmission demands due to traffic bursts, we propose a network bandwidth recovery method based on the Steiner tree to recover the network’s performance. Finally, the results of a simulation showed that the algorithms proposed in this article obtain an effective solution and that the heuristic algorithm requires less computing time.

Suggested Citation

  • Jintao Wang & Xi Jin & Peng Zeng & Ming Wan & Changqing Xia, 2017. "Deployment optimization for a long-distance wireless backhaul network in industrial cyber physical systems," International Journal of Distributed Sensor Networks, , vol. 13(11), pages 15501477177, November.
  • Handle: RePEc:sae:intdis:v:13:y:2017:i:11:p:1550147717744993
    DOI: 10.1177/1550147717744993
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1550147717744993
    Download Restriction: no

    File URL: https://libkey.io/10.1177/1550147717744993?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. Caleb C. Fast & Illya V. Hicks, 2017. "A Branch Decomposition Algorithm for the p -Median Problem," INFORMS Journal on Computing, INFORMS, vol. 29(3), pages 474-488, August.
    2. Colmenar, J. Manuel & Greistorfer, Peter & Martí, Rafael & Duarte, Abraham, 2016. "Advanced Greedy Randomized Adaptive Search Procedure for the Obnoxious p-Median problem," European Journal of Operational Research, Elsevier, vol. 252(2), pages 432-442.
    3. Kewang Zhang & Zhou Feng & Xin Li, 2016. "Weight-Based Link Scheduling for Convergecast in WirelessHART Network," International Journal of Distributed Sensor Networks, , vol. 12(7), pages 4594183-459, July.
    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. Miriam Kießling & Sascha Kurz & Jörg Rambau, 2021. "An exact column-generation approach for the lot-type design problem," TOP: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 29(3), pages 741-780, October.
    2. Drezner, Zvi & Kalczynski, Pawel & Salhi, Said, 2019. "The planar multiple obnoxious facilities location problem: A Voronoi based heuristic," Omega, Elsevier, vol. 87(C), pages 105-116.
    3. Vishwanath R. Singireddy & Manjanna Basappa, 2024. "Dispersing facilities on planar segment and circle amidst repulsion," Journal of Global Optimization, Springer, vol. 88(1), pages 233-252, January.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    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:sae:intdis:v:13:y:2017:i:11:p:1550147717744993. 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.