IDEAS home Printed from https://ideas.repec.org/a/spr/telsys/v88y2025i1d10.1007_s11235-025-01268-0.html
   My bibliography  Save this article

Superframe contention slot scheduling (SCSS): deep reinforcement learning-based time slot allocation for wireless body area network

Author

Listed:
  • Vamsi Kiran Mekathoti

    (National Institute of Technology)

  • B. Nithya

    (National Institute of Technology)

Abstract

Wireless Body Area Network (WBAN) grabs the attention of researchers as it is a needy technology for e-healthcare. Due to its limited protocol support, providing Quality of Service (QoS) is a challenging task. Despite the previous research, a critical research gap persists in superframe time slot allocation to avoid collisions among the Bio Sensor Nodes (BSNs). To address this, a robust Superframe Contention Slot Scheduling (SCSS) algorithm is proposed to identify potential BSNs to occupy slots under the Exclusive Access Period (EAP) slots of the superframe. It incorporates a Markov Decision Process (MDP) policy function to select these BSNs using several runtime operational parameters. The deep Reinforcement Learning (DRL) algorithm implements the MDP process to get the optimized rewards. The proposed algorithm adopts sleep schedules and energy harvesting techniques to avoid the dead nodes problem. A Two-state Markov Chain (TMC) model is adopted to theoretically analyze the expected throughput and loss performance. The comprehensive simulation results show a 41.8% improvement in throughput, a 42.62% reduction in packet loss, a 6.9% less energy consumption, and enhanced overall network performance compared to existing protocols.

Suggested Citation

  • Vamsi Kiran Mekathoti & B. Nithya, 2025. "Superframe contention slot scheduling (SCSS): deep reinforcement learning-based time slot allocation for wireless body area network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 88(1), pages 1-13, March.
    • Handle: RePEc:spr:telsys:v:88:y:2025:i:1:d:10.1007_s11235-025-01268-0
    DOI: 10.1007/s11235-025-01268-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11235-025-01268-0
    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/s11235-025-01268-0?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. Yousaf Zia & Fasial Bashir & Kashif Naseer Qureshi, 2020. "Dynamic superframe adaptation using group-based media access control for handling traffic heterogeneity in wireless body area networks," International Journal of Distributed Sensor Networks, , vol. 16(8), pages 15501477209, August.
    2. Linfeng Zheng & Juncheng Hu & Yingjun Jiao, 2023. "A Cross-Layer Media Access Control Protocol for WBANs," Sustainability, MDPI, vol. 15(14), pages 1-16, 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.

      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:telsys:v:88:y:2025:i:1:d:10.1007_s11235-025-01268-0. 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.