Today, modern telco infrastructures are espousing softwarized paradigms (e.g. virtualization, containerization), which are necessary to implement the network slicing, and, consequently, to achieve a beneficial trade-off between service offered and costs. In particular, container-based technologies, when compared to classic virtualized frameworks, offer a lightweight environment to host novel network services. Inspired by these last trends, in this work we propose a statistical characterization of a containerized version of IP Multimedia Subsystem (cIMS), one of the crucial parts of 5G core network. Precisely, we: i) exploit the Queueing Networks (QN) formalism to model the chained behavior of a cIMS infrastructure; ii) perform a statistical assessment aimed at analyzing both the queueing dynamics in different scenarios (single/multi class), and at selecting the optimal cIMS deployment guaranteeing the minimum response time at a given cost; iii) carry on an experimental analysis through Clearwater platform to extract realistic estimates of system parameters.

Statistical Characterization of Containerized IP Multimedia Subsystem through Queueing Networks

M. Di Mauro;M. Longo;F. Postiglione
2020-01-01

Abstract

Today, modern telco infrastructures are espousing softwarized paradigms (e.g. virtualization, containerization), which are necessary to implement the network slicing, and, consequently, to achieve a beneficial trade-off between service offered and costs. In particular, container-based technologies, when compared to classic virtualized frameworks, offer a lightweight environment to host novel network services. Inspired by these last trends, in this work we propose a statistical characterization of a containerized version of IP Multimedia Subsystem (cIMS), one of the crucial parts of 5G core network. Precisely, we: i) exploit the Queueing Networks (QN) formalism to model the chained behavior of a cIMS infrastructure; ii) perform a statistical assessment aimed at analyzing both the queueing dynamics in different scenarios (single/multi class), and at selecting the optimal cIMS deployment guaranteeing the minimum response time at a given cost; iii) carry on an experimental analysis through Clearwater platform to extract realistic estimates of system parameters.
2020
978-1-7281-5684-2
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4748183
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 2
  • ???jsp.display-item.citation.isi??? 0
social impact