Publication detail

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.

Original Title

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

Type

conference paper

Language

English

Original Abstract

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.

Keywords

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

Authors

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

Released

30. 12. 2020

Publisher

Springer

Location

Švýcarsko

ISBN

9783030657253

Book

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

Pages from

71

Pages to

85

Pages count

15

URL

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"
}