IDEAS home Printed from https://ideas.repec.org/a/spr/joinma/v32y2021i8d10.1007_s10845-020-01640-8.html
   My bibliography  Save this article

Mitigating congestion in wireless sensor networks through clustering and queue assistance: a survey

Author

Listed:
  • Saneh Lata Yadav

    (Guru Gobind Singh Indraprastha University, (USICT))

  • R. L. Ujjwal

    (Guru Gobind Singh Indraprastha University, (USICT))

Abstract

A network of randomly deployed sensor nodes which shares limited resources like bandwidth, buffer, queue, and battery powered nodes is known as wireless sensor network. Such network must have energy, to avoid the chances of congestion because congested network degrades the performance of network. Congestion may occur due to several reasons like data packet collision, transmission channel contention and buffer overflow. A congestion control protocol must acquire the functionalities that can increase the lifetime and efficiency of network which are major responsibilities of wireless sensor network. In this paper traffic oriented, resource oriented and a hybrid approach with some additional functionalities of controlling congestion are discussed in a wide manner. The hybrid approach is best as per this survey as it integrates various factors of wireless sensor networks to control and mitigate the situation. A comprehensive analysis is also done on these factors to justify the nature of different approaches.

Suggested Citation

  • Saneh Lata Yadav & R. L. Ujjwal, 2021. "Mitigating congestion in wireless sensor networks through clustering and queue assistance: a survey," Journal of Intelligent Manufacturing, Springer, vol. 32(8), pages 2083-2098, December.
  • Handle: RePEc:spr:joinma:v:32:y:2021:i:8:d:10.1007_s10845-020-01640-8
    DOI: 10.1007/s10845-020-01640-8
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10845-020-01640-8
    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/s10845-020-01640-8?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. Amin Shahraki & Marjan Kuchaki Rafsanjani & Arsham Borumand Saeid, 2017. "Hierarchical distributed management clustering protocol for wireless sensor networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 65(1), pages 193-214, May.
    2. Cosmena Mahapatra & Ashish Payal & Meenu Chopra, 2020. "Swarm intelligence based centralized clustering: a novel solution," Journal of Intelligent Manufacturing, Springer, vol. 31(8), pages 1877-1888, December.
    3. Gerardo Santillán Martínez & Ivan M. Delamer & José L. Martínez Lastra, 2017. "A packet scheduler for real-time 6LoWPAN wireless networks in manufacturing systems," Journal of Intelligent Manufacturing, Springer, vol. 28(2), pages 301-311, February.
    4. Bérenger Ossété Gombé & Gwenhael Goavec Mérou & Karla Breschi & Hervé Guyennet & Jean-Michel Friedt & Violeta Felea & Kamal Medjaher, 2019. "A SAW wireless sensor network platform for industrial predictive maintenance," Journal of Intelligent Manufacturing, Springer, vol. 30(4), pages 1617-1628, April.
    5. Ghasem Kahe & Amir Hossein Jahangir, 2019. "A self-tuning controller for queuing delay regulation in TCP/AQM networks," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 71(2), pages 215-229, June.
    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. Wladimir Gonçalves Morais & Carlos Eduardo Maffini Santos & Carlos Marcelo Pedroso, 2022. "Application of active queue management for real-time adaptive video streaming," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 79(2), pages 261-270, February.
    2. Muhammad Ilyas & Zahid Ullah & Fakhri Alam Khan & Muhammad Hasanain Chaudary & Muhammad Sheraz Arshed Malik & Zafar Zaheer & Hamood Ur Rehman Durrani, 2020. "Trust-based energy-efficient routing protocol for Internet of things–based sensor networks," International Journal of Distributed Sensor Networks, , vol. 16(10), pages 15501477209, October.
    3. Xuejun Zhao & Yong Qin & Changbo He & Limin Jia, 2022. "Underdetermined blind source extraction of early vehicle bearing faults based on EMD and kernelized correlation maximization," Journal of Intelligent Manufacturing, Springer, vol. 33(1), pages 185-201, January.
    4. Galina Samigulina & Zarina Samigulina, 2022. "Diagnostics of industrial equipment and faults prediction based on modified algorithms of artificial immune systems," Journal of Intelligent Manufacturing, Springer, vol. 33(5), pages 1433-1450, June.
    5. Marek Barczyk & Andrzej Chydzinski, 2022. "AQM based on the queue length: A real-network study," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-21, February.

    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:joinma:v:32:y:2021:i:8:d:10.1007_s10845-020-01640-8. 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.