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Analyzing the effectiveness of dynamic network slicing procedure in 5g network by queuing and simulation models

The result's identifiers

  • Result code in IS VaVaI

    <a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F20%3APU144168" target="_blank" >RIV/00216305:26220/20:PU144168 - isvavai.cz</a>

  • Result on the web

    <a href="https://link.springer.com/content/pdf/10.1007/978-3-030-65726-0.pdf" target="_blank" >https://link.springer.com/content/pdf/10.1007/978-3-030-65726-0.pdf</a>

  • DOI - Digital Object Identifier

    <a href="http://dx.doi.org/10.1007/978-3-030-65726-0_7" target="_blank" >10.1007/978-3-030-65726-0_7</a>

Alternative languages

  • Result language

    angličtina

  • Original language name

    Analyzing the effectiveness of dynamic network slicing procedure in 5g network by queuing and simulation models

  • Original language description

    In this paper, we propose three metrics that could be used for accessing the effectiveness of a dynamic Network Slicing. On the one hand re-slicing could result in more adaptive resource allocation for different virtual network operators (VNO), but could arise the signaling overhead. On the other hand an insufficient amount of re-slicing could significantly decrease the quality of service for VNO users, but reduce the signaling delays. Proposed metrics could be used for analyzing the abovementioned effect. We illustrate the metrics by the simulation model for a simple dynamic network slicing algorithm. We also propose a queuing system approach for analyzing dynamic network slicing for 2 VNOs.

  • Czech name

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    20201 - Electrical and electronic engineering

Result continuities

  • Project

  • Continuities

    O - Projekt operacniho programu

Others

  • Publication year

    2020

  • Confidentiality

    S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Data specific for result type

  • Article name in the collection

    Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

  • ISBN

    9783030657253

  • ISSN

  • e-ISSN

  • Number of pages

    15

  • Pages from-to

    71-85

  • Publisher name

    Springer

  • Place of publication

    Švýcarsko

  • Event location

    St. Petersburg

  • Event date

    Aug 26, 2020

  • Type of event by nationality

    WRD - Celosvětová akce

  • UT code for WoS article