Statistical Characterization of Containerized IP Multimedia Subsystem through Queueing Networks

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.