IDEAS home Printed from https://ideas.repec.org/a/gam/jftint/v14y2022i10p299-d946416.html
   My bibliography  Save this article

Modeling and Analyzing Preemption-Based Service Prioritization in 5G Networks Slicing Framework

Author

Listed:
  • Yves Adou

    (Applied Probability and Informatics Department, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Str., Moscow 117198, Russia)

  • Ekaterina Markova

    (Applied Probability and Informatics Department, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Str., Moscow 117198, Russia)

  • Yuliya Gaidamaka

    (Applied Probability and Informatics Department, Peoples’ Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya Str., Moscow 117198, Russia
    Federal Research Center “Computer Science and Control” of the Russian Academy of Sciences, 44-2 Vavilov Str., Moscow 119333, Russia)

Abstract

The Network Slicing (NS) technology, recognized as one of the key enabling features of Fifth Generation (5G) wireless systems, provides very flexible ways to efficiently accommodate common physical infrastructures, e.g., Base Station (BS), multiple logical networks referred to as Network Slice Instances (NSIs). To ensure the required Quality of Service (QoS) levels, the NS-technology relies on classical Resource Reservation (RR) or Service Prioritization schemes. Thus, the current paper aims to propose a Preemption-based Prioritization (PP) scheme “merging” the classical RR and Service Prioritization schemes. The proposed PP-scheme efficiency is evaluated or estimated given a Queueing system (QS) model analyzing the operation of multiple NSIs with various requirements at common 5G BSs. As a key result, the proposed PP-scheme can provide up to 100% gain in terms of blocking probabilities of arriving requests with respect to some baseline.

Suggested Citation

  • Yves Adou & Ekaterina Markova & Yuliya Gaidamaka, 2022. "Modeling and Analyzing Preemption-Based Service Prioritization in 5G Networks Slicing Framework," Future Internet, MDPI, vol. 14(10), pages 1-16, October.
    • Handle: RePEc:gam:jftint:v:14:y:2022:i:10:p:299-:d:946416
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1999-5903/14/10/299/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1999-5903/14/10/299/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Natalia Yarkina & Yuliya Gaidamaka & Luis M. Correia & Konstantin Samouylov, 2020. "An Analytical Model for 5G Network Resource Sharing with Flexible SLA-Oriented Slice Isolation," Mathematics, MDPI, vol. 8(7), pages 1-19, July.
    2. Ramraj Dangi & Akshay Jadhav & Gaurav Choudhary & Nicola Dragoni & Manas Kumar Mishra & Praveen Lalwani, 2022. "ML-Based 5G Network Slicing Security: A Comprehensive Survey," Future Internet, MDPI, vol. 14(4), pages 1-28, April.
    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. Meenakshi Kandpal & Niharika Keshari & Amrendra Singh Yadav & Mohit Yadav & Rabindra Kumar Barik, 2024. "Modelling of blockchain based queuing theory implementing preemptive and non-preemptive algorithms," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 15(6), pages 2554-2570, June.
    2. Daria Ivanova & Yves Adou & Ekaterina Markova & Yuliya Gaidamaka & Konstantin Samouylov, 2023. "Mathematical Framework for Mixed Reservation- and Priority-Based Traffic Coexistence in 5G NR Systems," Mathematics, MDPI, vol. 11(4), pages 1-15, February.

    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:gam:jftint:v:14:y:2022:i:10:p:299-:d:946416. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.