IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v298y2021i1d10.1007_s10479-018-2943-7.html
   My bibliography  Save this article

Optimization of wireless sensor networks deployment with coverage and connectivity constraints

Author

Listed:
  • Sourour Elloumi

    (ENSTA-ParisTech/UMA)

  • Olivier Hudry

    (Télécom-ParisTech/LTCI)

  • Estel Marie

    (Conservatoire National des Arts et Métiers/CEDRIC)

  • Agathe Martin

    (Conservatoire National des Arts et Métiers/CEDRIC)

  • Agnès Plateau

    (Conservatoire National des Arts et Métiers/CEDRIC)

  • Stéphane Rovedakis

    (Conservatoire National des Arts et Métiers/CEDRIC)

Abstract

Wireless sensor networks have been widely deployed in the last decades to provide various services, like environmental monitoring or object tracking. Such a network is composed of a set of sensor nodes which are used to sense and transmit collected information to a base station. To achieve this goal, two properties have to be guaranteed: (i) the sensor nodes must be placed such that the whole environment of interest (represented by a set of targets) is covered, and (ii) every sensor node can transmit its data to the base station (through other sensor nodes). In this paper, we consider the Minimum Connected k-Coverage (MCkC) problem, where a positive integer $$k \ge 1$$ k ≥ 1 defines the coverage multiplicity of the targets. We propose two mathematical programming formulations for the MCkC problem on square grid graphs and random graphs. We compare them to a recent model proposed by Rebai et al. (Comput Oper Res 59:11–21, 2015). We use a standard mixed integer linear programming solver to solve several instances with different formulations. In our results, we point out the quality of the LP-bound of each formulation as well as the total CPU time or the proportion of solved instances to optimality within a given CPU time.

Suggested Citation

  • Sourour Elloumi & Olivier Hudry & Estel Marie & Agathe Martin & Agnès Plateau & Stéphane Rovedakis, 2021. "Optimization of wireless sensor networks deployment with coverage and connectivity constraints," Annals of Operations Research, Springer, vol. 298(1), pages 183-206, March.
  • Handle: RePEc:spr:annopr:v:298:y:2021:i:1:d:10.1007_s10479-018-2943-7
    DOI: 10.1007/s10479-018-2943-7
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-018-2943-7
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-018-2943-7?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Abilio Lucena & Nelson Maculan & Luidi Simonetti, 2010. "Reformulations and solution algorithms for the maximum leaf spanning tree problem," Computational Management Science, Springer, vol. 7(3), pages 289-311, July.
    2. Bernard Gendron & Abilio Lucena & Alexandre Salles da Cunha & Luidi Simonetti, 2014. "Benders Decomposition, Branch-and-Cut, and Hybrid Algorithms for the Minimum Connected Dominating Set Problem," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 645-657, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kavita Jaiswal & Veena Anand, 2021. "A QoS aware optimal node deployment in wireless sensor network using Grey wolf optimization approach for IoT applications," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 78(4), pages 559-576, December.

    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. Austin Buchanan & Je Sang Sung & Sergiy Butenko & Eduardo L. Pasiliao, 2015. "An Integer Programming Approach for Fault-Tolerant Connected Dominating Sets," INFORMS Journal on Computing, INFORMS, vol. 27(1), pages 178-188, February.
    2. Li, Xiangyong & Aneja, Y.P., 2017. "Regenerator location problem: Polyhedral study and effective branch-and-cut algorithms," European Journal of Operational Research, Elsevier, vol. 257(1), pages 25-40.
    3. Hamidreza Validi & Austin Buchanan, 2020. "The Optimal Design of Low-Latency Virtual Backbones," INFORMS Journal on Computing, INFORMS, vol. 32(4), pages 952-967, October.
    4. Yıldız, Barış & Karaşan, Oya Ekin, 2015. "Regenerator Location Problem and survivable extensions: A hub covering location perspective," Transportation Research Part B: Methodological, Elsevier, vol. 71(C), pages 32-55.
    5. Xinyun Wu & Zhipeng Lü & Fred Glover, 2022. "A Fast Vertex Weighting-Based Local Search for Finding Minimum Connected Dominating Sets," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 817-833, March.
    6. Markus Leitner & Ivana Ljubić & Martin Riedler & Mario Ruthmair, 2019. "Exact Approaches for Network Design Problems with Relays," INFORMS Journal on Computing, INFORMS, vol. 31(1), pages 171-192, February.
    7. Vic Grout, 2017. "A Simple Approach to Dynamic Optimisation of Flexible Optical Networks with Practical Application," Future Internet, MDPI, vol. 9(2), pages 1-11, May.
    8. Adasme, Pablo & Andrade, Rafael Castro de, 2023. "Minimum weight clustered dominating tree problem," European Journal of Operational Research, Elsevier, vol. 306(2), pages 535-548.
    9. do Forte, Vinicius L. & Hanafi, Saïd & Lucena, Abilio, 2023. "Extended formulations for perfect domination problems and their algorithmic implications," European Journal of Operational Research, Elsevier, vol. 310(2), pages 566-581.
    10. Si Chen & Ivana Ljubić & S. Raghavan, 2015. "The Generalized Regenerator Location Problem," INFORMS Journal on Computing, INFORMS, vol. 27(2), pages 204-220, May.
    11. Barış Yıldız & Oya Ekin Karaşan, 2017. "Regenerator Location Problem in Flexible Optical Networks," Operations Research, INFORMS, vol. 65(3), pages 595-620, June.
    12. Eduardo Álvarez-Miranda & Markus Sinnl, 2020. "A branch-and-cut algorithm for the maximum covering cycle problem," Annals of Operations Research, Springer, vol. 284(2), pages 487-499, January.
    13. Roshanaei, Vahid & Luong, Curtiss & Aleman, Dionne M. & Urbach, David R., 2020. "Reformulation, linearization, and decomposition techniques for balanced distributed operating room scheduling," Omega, Elsevier, vol. 93(C).
    14. Roshanaei, Vahid & Naderi, Bahman, 2021. "Solving integrated operating room planning and scheduling: Logic-based Benders decomposition versus Branch-Price-and-Cut," European Journal of Operational Research, Elsevier, vol. 293(1), pages 65-78.
    15. Jiao Zhou & Zhao Zhang & Shaojie Tang & Xiaohui Huang & Ding-Zhu Du, 2018. "Breaking the O (ln n ) Barrier: An Enhanced Approximation Algorithm for Fault-Tolerant Minimum Weight Connected Dominating Set," INFORMS Journal on Computing, INFORMS, vol. 30(2), pages 225-235, May.
    16. Xiangyong Li & Y. P. Aneja, 2020. "A new branch-and-cut approach for the generalized regenerator location problem," Annals of Operations Research, Springer, vol. 295(1), pages 229-255, December.
    17. Buchanan, Austin & Sung, Je Sang & Boginski, Vladimir & Butenko, Sergiy, 2014. "On connected dominating sets of restricted diameter," European Journal of Operational Research, Elsevier, vol. 236(2), pages 410-418.
    18. Ruizhi Li & Shuli Hu & Huan Liu & Ruiting Li & Dantong Ouyang & Minghao Yin, 2019. "Multi-Start Local Search Algorithm for the Minimum Connected Dominating Set Problems," Mathematics, MDPI, vol. 7(12), pages 1-14, December.
    19. Bernard Gendron & Abilio Lucena & Alexandre Salles da Cunha & Luidi Simonetti, 2014. "Benders Decomposition, Branch-and-Cut, and Hybrid Algorithms for the Minimum Connected Dominating Set Problem," INFORMS Journal on Computing, INFORMS, vol. 26(4), pages 645-657, November.

    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:spr:annopr:v:298:y:2021:i:1:d:10.1007_s10479-018-2943-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.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.