Detail publikace

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

KOCHETKOVA, I. VLASKINA, A. BURTSEVA, S. SAVICH, V. HOŠEK, J.

Originální název

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

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

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.

Klíčová slova

Dynamic system; Efficiency indicators; Impatient elastic traffic; Two-service QS

Autoři

KOCHETKOVA, I.; VLASKINA, A.; BURTSEVA, S.; SAVICH, V.; HOŠEK, J.

Vydáno

30. 12. 2020

Nakladatel

Springer

Místo

Švýcarsko

ISBN

9783030657253

Kniha

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

Strany od

71

Strany do

85

Strany počet

15

URL

https://link.springer.com/content/pdf/10.1007/978-3-030-65726-0.pdf

BibTex

@inproceedings{BUT177424,
  author="Irina {Kochetkova} and Anastasia {Vlaskina} and Sofia {Burtseva} and Valeria {Savich} and Jiří {Hošek}",
  title="Analyzing the effectiveness of dynamic network slicing procedure in 5g network by queuing and simulation models",
  booktitle="Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics",
  year="2020",
  pages="71--85",
  publisher="Springer",
  address="Švýcarsko",
  doi="10.1007/978-3-030-65726-0\{_}7",
  isbn="9783030657253",
  url="https://link.springer.com/content/pdf/10.1007/978-3-030-65726-0.pdf"
}